Patent Publication Number: US-2023137222-A1

Title: Smart dumbbell

Description:
CROSS-REFERENCE TO RELATED PATENT APPLICATIONS 
     This application claims priority to and the benefit of U.S. Provisional Patent Application No. 63/273,775, titled “Smart Dumbbell” and filed Oct. 29, 2021, and this application is related to U.S. Pat. No. 10,758,780, issued Sep. 1, 2020 and titled “Reflective Video Display Apparatus for Interactive Training and Demonstration and Methods of Using Same,” and to U.S. Provisional Patent Application No. 63/273,737, filed Oct. 29, 2021 and titled “Smart Flexible Exercise Weight,” and to U.S. Design Patent Application No. 29/813,656, filed Oct. 29, 2021 and titled “Dumbbell With Ridged Plates,” the entire contents of each of which are incorporated herein by reference in their entireties. 
    
    
     FIELD 
     The present disclosure relates to systems for exercise equipment, and more specifically, to a smart dumbbell configured to communicate with a smart mirror. 
     BACKGROUND 
     Exercise is an important part of maintaining an individual&#39;s health and wellbeing. For many people, exercising is an activity that typically involves going to a gymnasium where they partake in a workout guided by an instructor (e.g., a fitness instructor, a personal trainer). However, dedicating a regular period of time to exercise at a gym can be a challenging endeavor due to other commitments in one&#39;s daily life (e.g., a person&#39;s job, family obligations). Oftentimes, a gym may be located at an inconvenient location and/or an instructor&#39;s availability is limited to certain periods of time during the day, thus limiting a person&#39;s ability to attend a workout at the gym. This inconvenience may also be detrimental to the instructor whose clientele may be restricted to people who are able to attend their workout at the gym at the prescribed period of time. 
     SUMMARY 
     In some embodiments, an apparatus includes a first weight plate, a second weight plate, and an elongate, substantially cylindrical handle. The first weight plate assembly includes a first pair of endplates and a first over-molded weight. The second weight plate assembly includes a second pair of endplates and a second over-molded weight. The handle is mechanically coupled at a first end to the first weight plate assembly and at a second end to the second weight plate assembly. At least one of the first weight plate assembly or the second weight plate assembly includes at least one light-emitting diode (LED) and a transparent or translucent numerical indicator associated with a total weight of the apparatus and through which light emitted from the at least one LED is transmitted when the at least one LED is activated. 
     In some embodiments, an apparatus includes a first weight plate assembly, a second weight plate assembly, and an elongate, substantially cylindrical handle. The first weight plate assembly includes a first pair of endplates and a first over-molded weight, and the second weight plate assembly includes a second pair of endplates and a second over-molded weight. The handle is mechanically coupled at a first end to the first weight plate assembly and mechanically coupled at a second end, opposite the first end, to the second weight plate assembly. Each of the first weight plate assembly and the second weight plate assembly has a perimeter surface that defines a double-ridge shape between the pair of endplates for that weight plate assembly. 
     In some embodiments, an apparatus includes a first weight plate assembly, a second weight plate assembly, and an elongate, substantially cylindrical handle. The first weight plate assembly includes a first pair of endplates and a first over-molded weight. The second weight plate assembly includes a second pair of endplates and a second over-molded weight. The handle is mechanically coupled at a first end to the first weight plate assembly and is mechanically coupled at a second end, opposite the first end, to the second weight plate assembly. At least one of the first weight plate assembly or the second weight plate assembly includes at least one light-emitting diode (LED). At least one of the first weight plate assembly or the second weight plate assembly including a processor operably coupled to a memory storing instructions to cause the processor to activate the at least one LED in response to detecting a status associated with at least one of the apparatus, a user of the apparatus, or a workout being performed by the user of the apparatus. 
     In some embodiments, a user of a smart mirror schedules a rebroadcast of a previously recorded fitness class, to be displayed concurrently via multiple smart mirrors associated with multiple multiplexed geographically remote users who are “invitees” to the rebroadcast. Non-invitees can be blocked from accessing the rebroadcast. During the rebroadcast, invitees and the user can view live video feeds of one another, and can communicate with one another using voice, text, and/or graphic symbols (e.g., emojis). The voice communications can occur via the microphones/speakers of the mirrors, and the text and/or graphic symbols can be displayed via the mirrors. Optionally, real-time biometric data of the user can be displayed via the user&#39;s smart mirror and/or via smart mirrors of other invitees. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram of a smart mirror, in accordance with some embodiments. 
         FIG.  2 A  shows a first example implementation of a smart mirror, in accordance with some embodiments. 
         FIG.  2 B  shows a second example implementation of a smart mirror, with an integrated stand, in accordance with some embodiments. 
         FIG.  2 C  shows a third, wall-mountable example implementation of a smart mirror, in accordance with some embodiments. 
         FIG.  3 A  is an example flow diagram showing multiplexed communications during a video rebroadcasting session, in accordance with some embodiments. 
         FIGS.  3 B- 3 C  show example display configuration for a video rebroadcasting session, in accordance with some embodiments. 
         FIG.  4    is a diagram showing an example locker room implementation, in accordance with some embodiments. 
         FIG.  5    is a diagram showing interrelatedness of certain biometric data parameters. 
         FIG.  6    is a rendering of a connected weight, including a dumbbell and a connector sensor, in accordance with some embodiments. 
         FIG.  7    is a photographic image of a connected weight, including a dumbbell and a connector sensor, in accordance with some embodiments. 
         FIG.  8    is a system diagram showing connected weights and smart mirrors, in accordance with some embodiments. 
         FIGS.  9 A- 9 I  are diagrams of example connected weight configurations, in accordance with some embodiments. 
         FIG.  10 A  is a diagram showing a perspective view of a smart dumbbell, in accordance with some embodiments. 
         FIGS.  10 B- 10 C  are diagrams showing left and right views, respectively, of the smart dumbbell of  FIG.  10 A . 
         FIG.  10 D  is a diagram showing a side view of the smart dumbbell of  FIG.  10 A . 
         FIG.  11    is a diagram showing an exploded view of a smart dumbbell, in accordance with some embodiments. 
         FIGS.  12 A- 12 D  are diagrams showing a smart dumbbell, in accordance with some embodiments. 
         FIGS.  13 A- 13 B  are photographs showing a set of smart dumbbells, in accordance with some embodiments. 
         FIGS.  14 A- 14 G  are example graphical user interface (GUI) displays showing the generation and display of a universal health score, in accordance with some embodiments. 
         FIGS.  15 A- 15 H  are example GUI displays showing the generation and display of a universal health score, in accordance with some embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     The demand for home fitness products has been increasing for years, and in the midst of widespread public health concerns arising from Covid-19, forcing many to self-quarantine, such demand, in particular for “interactive” home fitness products, has been further enhanced. Known approaches to interactive fitness, however, typically involve a user interacting with a software application running on a smartphone, making it difficult to coordinate movements with the ability to clearly view the instruction rendered via the smartphone screen. In addition, many known approaches to streaming fitness content (e.g., via smart televisions) are not interactive (i.e., they involve one-way delivery of streamable content to viewers), and can exhibit low and/or inconsistent video resolution/quality, bandwidth limitations, latency issues, reliability issues (e.g., video dropout) buffering delays, video stream stuttering, device incompatibilities, etc. Embodiments set forth herein overcome the foregoing limitations of known approaches to delivering fitness content in a variety of ways, as discussed in the sections that follow. 
     Smart Mirrors 
     A “smart mirror,” as used herein, refers to a two-way mirror (e.g., comprising glass) and an electronic display that is at least partially aligned with (and disposed behind, from the point of view of a user) the two-way mirror, such that the user can simultaneously view his/her own reflection and the imagery/video presented via the electronic display during operation of the smart mirror.  FIG.  1    is a block diagram of a smart mirror  100 , in accordance with some embodiments. The smart mirror  100  includes a single board computer (SBC)  110  that controls, at least in part, the operation of various subcomponents of the smart mirror  100  and to manage the flow of content to/from the smart mirror  100  (e.g., video content, audio from one or more instructors and/or users, biometric sensor data, etc.). The smart mirror  100  includes a display panel  120  configured to display video content and a graphical user interface (GUI) with which users may interact to control the smart mirror  100 , for example to view biometric feedback data and/or other visual content, to select content for display, etc. The smart mirror  100  also includes a camera  130  operably coupled to the SBC  110  and configured (e.g., under control of the SBC  110 ) to record or live stream video and/or images of a user (e.g., while the user is exercising during a workout session). An antenna  140  is operably coupled to the SBC  110  and configured to facilitate communications between the smart mirror  100  and another device (e.g., a remote compute device, one or more other smart mirrors, a remote control device, one or more biometric sensors, a wireless router, one or more mobile compute devices, etc.) by transmitting and receiving signals representing messages. The antenna  140  can include multiple transmitters and receivers each configured to transmit/receive at a specific frequency and/or using a specific wireless standard (e.g., Bluetooth®, 802.11a, 802.11b, 802.11g, 802.11n, 802.11 ac, 2G, 3G, 4G, 4G LTE, 5G). The antenna  140  may include multiple antennas that each function as a receiver and/or a transmitter to communicate with various external devices, such as a user&#39;s smart device (e.g., a computer, a smart phone, a tablet), a biometric sensor (e.g., a heart rate monitor, a vibration sensor, or any other sensor described herein), and/or a remote server or cloud server to stream or play video content. An amplifier  150  is operably coupled to the SBC  110 , a left speaker  152 , a right speaker  154 , and a microphone array with a digital signal processor  160 , The amplifier  150  is configured to receive audio signals from the SBC  110  and route them for subsequent output through the left speaker  152  and/or the right speaker  154 . The microphone array  160  can be configured to detect audio/voice, including voice commands and/or other voice inputs made by one or more users within sufficient proximity of the smart mirror  100 . For example, the microphone array  160  can detect voice commands to start/stop a workout, voice communications to the instructor, voice commands to turn the display panel on/off, voice commands to change a layout of the GUI, voice commands to trigger an invitation to another smart mirror user to participate in a workout session, etc. The microphone array  160  is operably coupled to, and controllable by, the SBC  110 . A switched-mode power supply (SMPS)  170  is coupled to the SBC  110  and coupled to relay (and, optionally, regulate delivery of) electrical power from an external electrical power supply system (e.g., a wall outlet) to the various components of the smart mirror  100 . A switch  180  may be coupled to the SMPS  170  and/or the microphone array  160  to switch the smart mirror  100  and the microphone array  160  on and off Although shown and described in  FIG.  1    as including a single board computer  110 , in other embodiments the smart mirror  100  can include one or multiple processors and one or multiple memories operably coupled to the one or multiple processors. 
     In some embodiments, the smart mirror  100  also includes one or more additional components not shown in  FIG.  1   . For example, the smart mirror  100  may include onboard memory storage (nonvolatile memory and/or volatile memory) including, but not limited to, a hard disk drive (HDD), a solid state drive (SDD), flash memory, random access memory (RAM), or a secure digital (SD) card. This onboard memory storage may be used to store firmware and/or software for the operation of the smart mirror  100 . As described above, the onboard memory storage may also be used to store (temporarily and/or permanently) other data including, but not limited to, video content, audio, video of the user, biometric feedback data, and user settings. The smart mirror  100  may also include a frame to mount and support the various components of the smart mirror  100 . 
     Smart mirrors of the present disclosure may be positioned or mounted within an environment (e.g., a user&#39;s home, a fitness studio) in a variety of ways.  FIG.  2 A  shows a first example implementation of a smart mirror, in accordance with some embodiments.  FIG.  2 B  shows a second example implementation of a freestanding smart mirror, with an integrated stand, in accordance with some embodiments.  FIG.  2 C  shows a third, wall-mountable example implementation of a smart mirror, in accordance with some embodiments.  FIGS.  2 A and  2 B  show the smart mirror mounted to a stand positioned at the bottom of the smart mirror. As can be seen in  FIG.  2 A , the smart mirror reflects (via a semi-reflective or partially reflecting surface thereof) an image of a user (here, taking a picture of the smart mirror with a smart phone) and the surrounding environment. The smart mirror of  FIG.  2 A  also displays video content through the semi-reflective or partially reflecting surface, such that the video content and the reflections of the user and the surrounding environment are concurrently viewable via the smart mirror. When the smart mirror is powered off, the smart mirror has a fully reflective appearance under ambient lighting. In some implementations, the smart mirror includes a partially reflecting section and a fully reflecting section (e.g., surrounding the partially reflecting section). 
     Video Rebroadcasting Sessions with Multiplexed Smart Mirror Communications (“Sweat Dates”) 
     In some embodiments, a previously-recorded (“archived”) video including fitness content is made available (e.g., via a cloud-based server) to, or is accessible by, a networked plurality of smart mirrors. The previously-recorded video can be a previously-aired or previously broadcast class from a library of classes stored in the cloud-based server or other storage repository. The previously-recorded video may have been captured “live” via a smart mirror camera, or may have been recorded offline (e.g., in a fitness recording studio). One or more users (“scheduler(s)”) of the smart mirrors can schedule a broadcasting or rebroadcasting “session” (hereinafter “video rebroadcasting session”) of the previously-recorded video during a specified time interval, and invite other smart mirror users from a selected group of other smart mirror users (invitees) to join the session and watch the broadcast/rebroadcast simultaneously during the specified time interval. By interacting with a software application (“app”) running on a mobile device (e.g., a smartphone) and/or a smart mirror, the scheduler(s) can specify one or more of the following parameters for the video rebroadcasting session (“session data”): a start date, a start time, an end date, an end time, identifiers of user(s) that are invited to participate in the video rebroadcasting session (“invitees”), overlays to be presented to the invitees during the video rebroadcasting session, etc. The invitees can include all subscribers or users of smart mirrors within a networked community of smart mirrors, or a subset thereof. In some implementations, non-invitee smart mirror users are blocked from joining the video rebroadcasting session (e.g., by setting a “rule” that is stored in the cloud-based server or another repository accessible by and used by the app). 
     During the video rebroadcasting session, the scheduler and the invitees position themselves near their respective smart mirrors and view the previously-recorded video, which is displayed concurrently on the smart mirrors of all invitees, while simultaneously viewing “live” (i.e., real-time or substantially real-time) video of themselves and, optionally, the scheduler and/or one or more other invitees. Also during the video rebroadcasting session, the scheduler and the invitee(s) can interact with one another via their respective smart mirrors, e.g., visually (e.g., by gesturing within the field of view of the cameras of their respective smart mirrors, the gestures being viewable via the smart mirror(s) or one or more invitees), images (e.g., causing display of photos/images on smart mirrors of one or more invitees), voice (e.g., via the microphone(s) and speaker(s) of their respective smart mirrors), and/or by inputting feedback via the app (e.g., via a graphical user interface (GUI) of the app running on their smart mirror and/or via a GUI of the app running on their smartphone). As such, the smart mirrors, the scheduler, and the invitees (some or all of which are geographically remote from one another), as well as their communications with one another, are multiplexed within a networked system (e.g., as shown and discussed with reference to  FIG.  3 A , below). The feedback can include text and/or graphic symbols (e.g., emojis) that is subsequently displayed via the app of one or more invitees (e.g., via a GUI of the app running on their smart mirror and/or via a GUI of the app running on their smartphone).The disclosed system therefore facilitates multiplexed communications between and among the scheduler and the invitees, who may be geographically remote from one another. Optionally, real-time biometric data of the scheduler and/or the invitees can be displayed via a smart mirror of the scheduler and/or the invitees. 
       FIG.  3 A  is an example flow diagram showing multiplexed communications associated with scheduling and hosting a video rebroadcasting session, in accordance with some embodiments. As shown in  FIG.  3 A , each of multiple smart mirrors ( 300 A,  300 B,  300 C and  300 D) and an optional studio compute device  301  can communicate with a centralized server  310  (e.g., a cloud-based server including a processor and a memory storing processor-executable instructions to perform method steps described herein) via a network “N.” The network N can be a fully wireless telecommunications network, a fully wired telecommunications network, or a combination of both. The studio compute device  301  can be a desktop computer, laptop computer, tablet and/or smartphone, and can be located in a recording studio or other location suitable for recording video and audio for live and/or subsequent broadcast. The smart mirrors  300 A,  300 B,  300 C and  300 D can be similar to, or include some or all of the components of, the smart mirror  100  of  FIG.  1   . As shown in  FIG.  3 A , each of the smart mirrors  300 A,  300 B,  300 C and  300 D includes a processor  302 , communications component(s)  303  (e.g., one or more antennas, transceivers, etc.), a memory  304 , a video camera  305 , and at least one microphone (e.g., a microphone array)  307 . Each memory  304  stores an instance of a shared software application (“app”  304 A), settings  304 B (e.g., user-customizable settings for that smart mirror), session data  304 C (e.g., including data associated with past video rebroadcasting sessions and/or future video rebroadcasting sessions), user profile data  304 D for the user(s) associated with that smart mirror, and optionally a feedback archive  304 E and/or account data and permissions  304 F. The studio compute device  301  includes a processor  302 , communications component(s)  303  (e.g., one or more antennas, transceivers, etc.), a memory  304 , a video camera  305 , and at least one microphone (e.g., a microphone array)  307 . The memory  304  of the studio compute device  301  stores session data  304 C, video(s)  315 , and, optionally, an instance of the shared software application (“app”  304 A). The session data  304 C can include, for example, one or more of: class name(s), instructor name(s), original recording date, original recording time, number of times rebroadcast (i.e., number of previous video rebroadcasting sessions and/or future video rebroadcasting sessions), scheduled future rebroadcast date(s), scheduled future rebroadcast time(s), scheduled future rebroadcast duration(s), scheduled future rebroadcast participants/invitees, scheduled future rebroadcast scheduler(s), etc. In some implementations, the studio compute device  301  is a smart mirror. 
     According to some embodiments, prior to scheduling a video rebroadcasting session, one or more videos  315  (optionally recorded via the camera  305  of the studio compute device by an instructor user of the studio compute device  301 ) are sent to the server  310 , via the network N, from the studio compute device  301 . The one or more videos  315  can be stored in a memory of the server  310  for later retrieval by one or more users of the smart mirrors  300 A,  300 B,  300 C and  300 D. The users of the smart mirrors  300 A,  300 B,  300 C and  300 D can also browse the one or more videos  315  stored in the memory of the server  310  via the shared app  304  on their respective smart mirrors and/or via instances of the shared app  304  running on their respective smart phones or other mobile compute device(s). Although the one or more videos  315  are shown and described, with reference to  FIG.  3 A , as being sent to the server  310  from (and optionally recorded via) the studio compute device  301 , alternatively or in addition, the one or more videos  315  can be sent to the server  310  from (and optionally recorded via) one or more of the smart mirrors  300 A- 300 D. In such embodiments, the one or more videos can features the user(s) (e.g., performing workouts) rather than an instructor. 
     As shown in  FIG.  3 A , the scheduling of a video rebroadcasting session begins with a session request  320  sent from one of the networked smart mirrors (in this case, smart mirror  300 B), via the network N, to the server  310 . The session request  320  can be generated and sent in response to an input or interaction of a user of the smart mirror  300 B via the shared app  304  running on the smart mirror  300 B and/or via an instance of the shared app  304  running on the smart phone or other mobile compute device of the user. A user (or a smart mirror associated with that user) that causes generation of a session request  320  can be referred to as a “scheduler.” The session request  320  can include one or more video identifiers associated with the videos  315 , one or more user identifiers associated with the scheduler(s), and/or representations of one or more: class names, instructor names, original recording dates, original recording times, number of times rebroadcast (i.e., number of previous video rebroadcasting sessions and/or future video rebroadcasting sessions), skill levels, muscle groups, requested future rebroadcast date(s), requested future rebroadcast time(s), requested future rebroadcast duration(s), requested future rebroadcast participants/invitees, etc. The server  310  can maintain a local calendar or other schedule of past, current and/or future video broadcasts and rebroadcasts. The server  310 , upon receiving (and in response to) the session request  320 , can compare data from the session request with data stored in the memory of the server  310  to determine whether the requested video rebroadcasting session can be scheduled. If so, the server  310  may store, in the calendar or other schedule, a new data record associated with the video rebroadcasting session. Also in response to receiving the session request, the server  310  generates and sends, to the smart mirror  300 B and via the network N, a session acknowledgment message  322 . The session acknowledgment message  322  can include an indication as to whether the video rebroadcasting session has been approved/scheduled, a confirmation number for the request and/or acknowledgment, and if scheduled, scheduling information. Optionally, if a requested video rebroadcasting session has not been scheduled, or has been disapproved, the session acknowledgment message  322  can include suggestions for alternative scheduling, e.g., including any of the data types included in the session request. 
     If the smart mirror  300 B receives a session acknowledgment message  322  indicating that the video rebroadcasting session has not been scheduled, one or more session requests  320  may be sent from the smart mirror  300 B to the server  310 , in response to one or more of: a user selection of new session details made via the shared app, a user selection of a suggested alternative scheduling made via the shared app, or an automatic instruction generated by the smart mirror  300 B based on a rule within the settings  304 B of the smart mirror  300 B. 
     If the session acknowledgment message  322  indicates that the video rebroadcasting session has been scheduled, the server  310  (and/or the smart mirror  300 B or a mobile device operably coupled thereto) can send, either subsequently to or concurrently with sending the session acknowledgment message  322 , invitation messages to smart mirrors associated with users that are invited to the scheduled video rebroadcasting session (e.g., as specified by the session request  320 ). In this case, invitations  324 A,  324 B and  324 C are sent to smart mirrors  300 A,  300 C and  300 D, respectively. Once received at the respective smart mirrors, the invitations can trigger the display, via the shared app  304 A of the smart mirrors and/or via the shared app  304 A of mobile devices (optionally operably coupled to the smart mirrors), a user-selectable option to accept an invitation to join the scheduled video rebroadcasting session. Response messages  325 A,  325 B and  325 C are generated based on the users&#39; selections, and sent back to the server  310  which, in turn, can update the new data record associated with the video rebroadcasting session, to indicate a participation status (e.g., “accepted” or “declined”) for each of the users and/or smart mirrors. At the scheduled session start time, the server  310  can initiate and transmit a session feed (e.g., session feeds  326 A,  326 B,  326 C and/or  326 D), or a streamed version of the video(s) associated with the one or more video identifiers of the session request, to each smart mirror associated with an “accepted” participation status. Note that in some implementations, the scheduler(s) is automatically assigned an “accepted” participation status and sent the session feed during the video rebroadcasting session, while in other implementations the scheduler(s) is not automatically assigned an “accepted” participation status and/or the session request  320  includes a representation of a participation status for the scheduler(s). During the video rebroadcasting session, the session feeds  326 A,  326 B,  326 C and/or  326 D cause display of the video(s) associated with the one or more video identifiers of the session request via the associated smart mirrors  300 A,  300 C,  300 D and/or  300 B. Also during the video rebroadcasting session, users of the smart mirrors  300 A,  300 C,  300 D and/or  300 B can send feedback ( 328 A,  328 B,  328 C and/or  328 D, respectively) to the smart mirror(s) of one or more other invitees, optionally subject to settings  304 B and/or permissions  304 F of the smart mirror(s) of one or more other invitees. The feedback can include text, images, graphics (e.g., emojis), voice and/or video that is displayed or otherwise delivered via the smart mirror(s) (and/or associated mobile device(s)) of the recipient(s). Optionally, feedback that is sent or exchanged during the video rebroadcasting session is stored in the feedback archive(s)  304 E by the smart mirror(s) of one or more smart mirrors ( 300 A,  300 C and/or  300 D) of the invitees. The feedback can be stored in the feedback archive(s)  304 E in the form of records that include feedback date/time data, sender data, recipient data, session data and/or other data associated with the feedback, such that the feedback can subsequently be retrieved, viewed and/or displayed. The sender data can include sender identifier(s), sender biometric data, sender location data, sender fitness level data, etc. Similarly, the recipient data can include recipient identifier(s), recipient biometric data, recipient location data, recipient fitness level data, etc. 
       FIGS.  3 B- 3 C  show example display configuration for a video rebroadcasting session, in accordance with some embodiments. In a first embodiment, shown in  FIG.  3 B , while a session feed  326 A- 326 D is being transmitted/fed to the smart mirrors  300 A- 300 D during the video rebroadcasting session described with reference to  FIG.  3 A , a user “U” of a given smart mirror (e.g., smart mirror  300 B) can view, concurrently and in/on a common surface of the smart mirror: (1) a reflection of himself/herself (“U”), (2) the video feed showing the pre-recorded video (e.g., including an instructor “INST”), and optionally (3) live video of one or more other invitees (here, “INV-1” through “INV-3”), captured by the smart mirrors ( 300 A,  300 C and/or  300 D) of those invitees. As shown in  FIG.  3 B , the invitees can be presented in discrete panes arranged within the display of the common surface of the smart mirror. The panes can be arranged in a horizontal row along a smaller of a height or width of the smart mirror (as shown in  FIG.  3 B ), or alternatively in a horizontal row along a larger of the height or width of the smart mirror, in a vertical row along a smaller of the height or width of the smart mirror, in a vertical row along a larger of the height or width of the smart mirror, or in any other (optionally user-specified and/or reconfigurable) configuration. Optionally, the smart mirror has touch-screen functionality, such that user “U” can select (by touching the image of) one of the other invitees “INV-1” through “INV-3” to cause the associated live video pane to be resized (e.g., enlarged, reduced) within the smart mirror display, to close (i.e., stop display of) the associated live video pane, etc. Alternatively or in addition, the user U can view some or all components of the video rebroadcasting session via an instance of the shared app on his/her mobile compute device and interact with the video panes using the associated GUI of the mobile compute device, such that the video panes are resized or closed on the smart mirror. In other words, in response to a user manipulation of a video pane in a GUI of his//her mobile compute device, the shared app can cause the smart mirror to adjust the way that the video pane is rendered on the smart mirror. 
     In a second embodiment, shown in  FIG.  3 C , while a session feed  326 A- 326 D is being transmitted/fed to the smart mirrors  300 A- 300 D during the video rebroadcasting session described with reference to  FIG.  3 A , a user “U” of a given smart mirror (e.g., smart mirror  300 B) can view, concurrently and in/on a common surface of the smart mirror that may be oriented in a “landscape” format (i.e., the width is larger than the height): (1) a reflection of himself/herself (“U”), (2) the video feed showing the pre-recorded video (e.g., including an instructor “INST”), and optionally (3) live video of one or more other invitees (here, “INV- 1 ” through “INV-3”), captured by the smart mirrors ( 300 A,  300 C and/or  300 D) of those invitees. As shown in  FIG.  3 C , the live video images of the invitees can be presented within the common surface of the smart mirror (not in panes) and arranged (e.g., dimensioned) such that the invitees are similar in size to, or at least 50% the size of, the size of the reflected image of user U, thereby simulating a live “class” environment. As also shown in  FIG.  3 C , one or more “guest” users may be sufficiently permissioned (or request permission in realtime) to join an ongoing video rebroadcasting session, and may be labelled as such within the smart mirror display. Similar to the embodiment of  FIG.  3 B , the smart mirror optionally has touch-screen functionality, such that user “U” can select (by touching the image of) one of the other invitees “INV-1” through “INV-3” to cause the associated live video to be resized (e.g., enlarged, reduced) within the smart mirror display, to close (i.e., stop display of) the associated live video, etc. Alternatively or in addition, the user U can view some or all components of the video rebroadcasting session via an instance of the shared app on his/her mobile compute device and interact with the live video of the invitees using the associated GUI of the mobile compute device, such that the live video images are resized or closed on the smart mirror. In other words, in response to a user manipulation of a live video image in a GUI of his//her mobile compute device, the shared app can cause the smart mirror to adjust the way that the live video is rendered on the smart mirror. 
     Camera Activation in Mirror Device 
     In some embodiments, a live video/camera feed of a first smart mirror (e.g., smart mirror  100  of  FIG.  1   ) from a networked plurality of smart mirrors (e.g., smart mirrors  300 A- 300 D of  FIG.  3 A ) is transmitted (as a “live stream”) to one or multiple other smart mirrors from the networked plurality of smart mirrors, for example via a wired or wireless network (e.g., network N of  FIG.  3 A ) and via a server (e.g., server  310  of  FIG.  3 A ). The live streaming can be selectively turned on and off by the user of the first smart mirror and/or by the users of the one or multiple other smart mirrors from the networked plurality of smart mirrors, for example, according to permissions. The action of turning on or off the live stream can be in response to one or more of: an interaction by a user with an instance of a shared app on the smart mirror, an interaction by a user with an instance of a shared app on a mobile compute device, a voice/nose command made by a user via an instance of a shared app on the smart mirror, a voice/noise command made by a user via an instance of a shared app on a mobile compute device, a gesture command made by a user via an instance of a shared app on the smart mirror, a gesture command made by a user via an instance of a shared app on a mobile compute device, etc. The live stream can be captured by one or more smart mirrors from the streaming feed to produce captured video, and the captured video can be modified post-capture to remove and/or to add graphical elements, thereby producing modified captured video. The graphical elements can be images or animations that modify the user or the environment around the user (e.g. obscuring a user&#39;s background, modifying a user&#39;s appearance, overlaying one or more filters, and/or adding one or more dynamic effects (e.g., an augmented reality (AR) feature such as a pet or a crackling fire)). The captured video and/or the modified captured video can be sent from the smart mirror(s) to a remote server (e.g., a cloud server, such as server  310  in  FIG.  3 A ), for example for subsequent retrieval, rebroadcast, etc. 
     Encouragement Messaging: 
     In some embodiments, during a workout session, a video rebroadcasting session, and/or a “locker room” session (discussed further below), smart mirror users can cause the display of encouragement messages (e.g., including text, images, video, graphics (e.g., emojis), gestures, voice, animation, etc.) to be displayed in the smart mirrors and/or mobile compute devices (e.g., via a GUI of a shared app running thereon) of other smart mirror users within a networked plurality of smart mirrors. The encouragement messages can be generated and sent from a sender compute device (e.g., smart mirror, app, or smartphone) in response to an input or interaction of a user of a given smart mirror via a shared app running on that smart mirror and/or via an instance of the shared app  304  running on a smart phone or other mobile compute device of the user. Encouragement messages can be sent between individual users (i.e., one-to-one), for example between workout session participants and/or between an instructor and a workout session participant, or from a single user to multiple users, up to the entire community of users (i.e., one-to-many). Encouragement messages can be stored in memory, e.g., in the form of records that include feedback date/time data, sender data, recipient data, session data, workout data, maliciousness score(s), offensiveness score(s), sentiment score(s), and/or other data associated with the encouragement messages, such that the encouragement messages can subsequently be retrieved, viewed and/or displayed. The encouragement messages can be stored automatically, according to a user-defined rule, and/or in response to a user request. The encouragement messages can be stored in a memory of one or more smart mirrors, one or more remote servers (e.g., cloud servers), and/or one or more mobile compute devices. 
     Encouragement messages, once received at smart mirrors and/or mobile compute devices, may first be inspected, and a determination may be made as to whether the sender, a smart mirror or mobile compute device of the sender (i.e., a sender device), and/or the message contents are sufficiently permissioned or have previously been “whitelisted” such that they may be delivered or presented to the intended recipient. For example, the smart mirror and/or mobile compute device, via a processor thereof and/or via a shared app, can perform one or more of the following inspections/checks: analyze the message contents to determine a maliciousness score, analyze the message contents to determine an offensiveness score, analyze the message contents to determine a sentiment score, evaluate the message contents based on a set of rules or permissions, compare a sender identifier to stored sender data to determine whether the associated sender has been whitelisted, blacklisted, or has one or more associated permissions, compare a sender device identifier to stored device data to determine whether the associated sender device has been whitelisted, blacklisted, or has one or more associated permissions, etc. After the inspections/checks have been performed, the smart mirror and/or mobile compute device, via a processor thereof and/or via a shared app, can perform one or more of the following remediation actions: block delivery of the encouragement message to the recipient (e.g., prevent display of the encouragement message), send a reply message to the sender to indicate that the encouragement message has not been delivered, etc. The remediation actions can be performed in response to one or more triggers, which can include, but are not limited to: a maliciousness score exceeding a predefined, user-customizable threshold, detecting that the sender is has been blacklisted, detecting that the sender device has been blacklisted, detecting a rule that prevents delivery of messages from the sender, detecting a rule that prevents delivery of messages from the sender device, detecting a rule that prevents delivery of messages containing one or more predefined, user-customizable keywords, detecting a rule that prevents delivery of messages containing profanity, etc. 
     As used herein, a maliciousness score can be a numerical score that is generated using a machine learning algorithm configured to detect malware, spyware, spam and other unwanted messages. As used herein, an offensiveness score can refer to a numerical score that is generated based on one or more of: a linguistic model, one or more previous ratings assigned by the intended recipient user, a user-customizable sensitivity score associated with the intended recipient user, etc. As used herein, a sentiment score can refer to a numerical score (including positive values and negative values) generated by a machine learning model, the numerical score representing an overall sentiment or tone (e.g., angry, menacing, passive-aggressive, sarcastic, encouraging, happy, etc.) of an input message. 
     In some embodiments, encouragement messages are sent after a sender-specified time delay or at a sender-specified scheduled date/time or period (e.g., during a class scheduled for the next day). Alternatively or in addition, the display of encouragement messages received at a smart mirror (or app thereof) of a recipient may be delayed by, or blocked for, a recipient-defined period of time or until a user-defined event occurs or has transpired (e.g., after class to avoid distraction). 
     In some embodiments, encouragement messages are sent automatically to a first smart mirror (e.g., from a server and/or from one or more other smart mirrors), in response to detecting that one or more predefined conditions have been meet and/or that one or more rules have been satisfied. Examples of rules can include, but are not limited to: a rule to send encouragement messages to recipients that are friends and that that have set a new record within a predetermined preceding time period; a rule to send an encouragement message to a recipient in response to detecting that a performance metric (e.g., heart rate, intensity, breathing rate, cadence, power, etc.) of the recipient has reduced by at least a predetermined percentage within a predetermined period of time; a rule to send an encouragement message to a recipient in response to detecting that a workout session in which the recipient is participating is within a predetermined of time of an end time of the workout session (e.g., nearing the end of the workout session or a high-intensity portion thereof), a rule to randomly send encouragement messages (e.g., the timing, recipient and/or contents of the encouragement messages can be randomly selected), etc. Examples of conditions can include, but are not limited to: the existence of a friend relationship between the sender and the receiver; the existence of one or multiple social media connections between the sender and the receiver; fewer than a predetermined number of encouragement messages sent within a preceding predetermined period of time, etc. 
     In some embodiments, encouragement messages can be configured to “persist” within a GUI of the recipient (e.g., in the smart mirror of the recipient and/or in a smartphone or other mobile device of the recipient). As used herein, “persist” can refer to the continuous display for a predetermined extended period of time (e.g., greater than one minute, greater than five minutes, greater than ten minutes, for the duration of a workout session, until the smart mirror is turned off, or indefinitely) and/or until closed or minimized by the recipient. For example, in some such embodiments, an encouragement message is configured to display as a banner having at least one dimension that is the same as a width or a height of the smart mirror and/or having at least one dimension that is the same as a width or a height of the display panel of the smart mirror. In some such implementations, an encouragement message (e.g., in the form of a banner) persists within a portion of a display panel of a smart mirror when the remainder of the display panel is no longer displaying video (i.e., the remainder of the display panel has a mirror appearance). 
     In some embodiments, a smart mirror (or an app thereof) is configured to convert one or more encouragement messages, received from a sender from a first, as-received format, to a user-defined (i.e., recipient-defined) format that is different from the as-received format, either based on one or more rules stored in memory or based on an input received at the smart mirror and/or via the app from the user/recipient. Examples of as-received formats and user-defined formats include, but are not limited to: text, image, bitmap (e.g., Graphics Interchange Format (“GIF”)), animated GIF, video, audio, haptic/vibration feedback, Adobe Flash, watermark, etc. In some such embodiments, the rules stored in memory and/or the input from the user/recipient include instructions to present the encouragement messages using one of a display panel or a speaker of the smart mirror, or to cause communication of the encouragement messages to a recipient using an antenna of the smart mirror (e.g., by transmitting a signal to one or more compute devices, apps, or smart accessories in network communication with the smart mirror). 
     As a first example, a received encouragement message including a visual hand clap emoji can be converted to an audio hand clap that is played via the left speaker and/or the right speaker of the smart mirror. As a second example, a received encouragement message including a text message can be converted to a graphic image that is displayed via the display panel of the smart mirror. As a third example, a received encouragement message including an audio file (e.g., including a representation of speech or of sounds such as clapping) can be converted to text that is displayed via the display panel of the smart mirror. As a fourth example, a received encouragement message including image data can be converted to a GIF that is displayed via the display panel of the smart mirror. As a fifth example, a received encouragement message including graphic image data (e.g., an emoji) can be converted to a signal that is sent, via an antenna of the smart mirror, to an app running on a smart phone of the recipient, to cause display of a reduced-size image based on the graphic image data. As a sixth example, a received encouragement message including a text message can be converted to a signal that is sent, via an antenna of the smart mirror, to a wearable electronic accessory of the recipient (e.g., a bracelet) to cause a vibration (e.g., in a predefined pattern, with a predefined intensity, etc.) of the wearable electronic accessory. As a seventh example, a received encouragement message including a text message can be converted to a log file that is stored within a memory of the smart mirror (or in a remote server communicatively coupled to the smart mirror), for later retrieval/viewing. As an eighth example, a received encouragement message including a text image and/or image file can be converted into a social media post that is sent, via an app, for posting on one or multiple social media platforms (e.g., according to one or more predefined rules, which may specify privacy settings, post timing, automatic caption generation, rules for tagging other social media users, etc.). 
     In some embodiments, the smart mirror, app and/or mobile compute device associated with the smart mirror is configured to automatically generate and send a reply message (e.g., including another encouragement message, acknowledging receipt of the encouragement message, expressing gratitude for the encouragement message, etc.) to the sender compute device associated with the encouragement message. 
     In some embodiments, the smart mirror, app and/or mobile compute device stores rules or filters configured to block delivery, display, or presentation of an encouragement message in response to determining that a sentiment score, calculated for the encouragement message, is associated with an overall sentiment or tone of for example angry, menacing, passive-aggressive, or sarcastic. 
     In some embodiments, a smart mirror, app and/or mobile compute device can store rules or filters configured to block sending, delivery, display, or presentation of an encouragement message in response to detecting one or more predefined recipient conditions, which may include (but are not limited to): poor performance in a workout (e.g., a performance metric, optionally correlated to one or more biometric data values, such as speed, range of motion, muscle activation, etc. being below a predefined threshold value), injury (e.g., during a workout), distress, heart rate above a predefined threshold, etc. The one or more predefined recipient conditions can be detected based on live video data associated with the recipient (e.g., gathered via the smart mirror and/or the mobile compute device), sensor data gathered by one or more wearable electronic accessories (e.g., received at the smart mirror and/or the mobile compute device), etc. 
     In some embodiments, an instructor provides input to his/her smart mirror and/or mobile compute device (e.g., via voice, video gesturing, touch interaction with a graphical user interface, etc.) to cause display, within a display panel or GUI of a plurality of smart mirrors and/or mobile compute devices of a subset of workout participants, a request or suggestion for the subset of workout participants to send encouragement messages to at least one other workout participant not included in the subset of workout participants. 
     In some embodiments, encouragement messages received for a given recipient user of a smart mirror can be stored (e.g., in memory of the smart mirror and/or in a memory of a cloud server or other remote compute device communicably coupled with the smart mirror, app and/or mobile compute device of the user), as “encouragement data,” and tracked over time. The encouragement data can be compared to other real-time and/or stored data associated with the user, such as sensor data, workout performance data, workout data (e.g., type, intensity, instructor, number of participants, targeted muscle groups, etc.), social media data, biometric data, etc. to determine the effectiveness of the (historical) encouragement messages. Based on the determined effectiveness of the historical encouragement messages, the smart mirror and/or app (optionally using one or more artificial intelligence (AI) (e.g., machine learning) algorithms) can determine encouragement message types and/or encouragement message delivery timing that are deemed to be most effective in helping/encouraging the recipient user. 
     Challenge (“Face-Off”) Workouts 
     In some embodiments, a first user of a first smart mirror in a first location can send a “challenge” request (e.g., by interacting with a GUI of the first smart mirror or by interacting with a GUI of a first mobile compute device of the first user) to a second user of a second smart mirror in a second location (the second smart mirror being different from the first smart mirror and the first location being different from the second location). The challenge request is then displayed via a GUI of the second smart mirror (and/or via a GUI of a second mobile compute device of the second user), and the second user can accept or deny the challenge request via the same GUI(s). If the second user denies the challenge request, a “denied” response is sent back to the first smart mirror and/or the first mobile compute device. If the second user accepts the challenge request, an “accepted” response is sent back to the first smart mirror and/or the first mobile compute device, and a challenge workout (e.g., selected by the first user, as part of the challenge request generation) is simultaneously or substantially simultaneously displayed via both the first smart mirror and the second smart mirror, optionally at a mutually agreed later time. 
     During the challenge workout, video of the first user, obtained via one or more video cameras of the first smart mirror and/or via camera(s) of the first mobile compute device, and/or audio of the first user, obtained via one or more microphones of the first smart mirror and/or via microphone(s) first mobile compute device, are live streamed to the second smart mirror and displayed via the display panel of the second smart mirror. Similarly, during the challenge workout, video of the second user, obtained via one or more video cameras of the second smart mirror, and/or audio of the first user, obtained via one or more microphones of the first smart mirror, are live streamed to the first smart mirror and displayed via the display panel of the first smart mirror. As such, during the challenge workout, the first user and the second user can see themselves and their challenger (i.e., the other user) in their respective smart mirrors. Also during the workout, each of the first smart mirror and the second smart mirror (e.g., via the app running on the smart mirror) can: analyze and/or record video of the first user, analyze and/or record video of the second user, receive (and, optionally, analyze) biometric data from one or more wearable electronic accessories of the first user, and/or receive (and, optionally, analyze) biometric data from one or more wearable electronic accessories of the second user, to determine scores for the first user and the second user, and to identify a winner of the challenge workout based on the scores. In some embodiments, the scores can include numeric values that are associated with, or calculated based on, the biometric data, but that do not include the biometric data itself. For example, a heartrate within a first range may be assigned a score of “1,” whereas a heartrate within a second range may be assigned a score of “2.” In other embodiments, the scores can include non-numeric values (e.g., letters, characters, symbols, graphics, images, etc.). For example, a breathing rate within a first range may be assigned a score of “A,” whereas a breathing rate within a second range may be assigned a score of “B.” The winner of the challenge workout can be displayed (as text, image(s) and/or audio output) via a GUI of the first smart mirror (and/or the first mobile compute device), displayed (as text, image(s) and/or audio output) via the second smart mirror (and/or the first mobile compute device), and saved in at least one memory (e.g., of the first smart mirror, the second smart mirror, a cloud-based server or other remote server, etc.) for later retrieval and viewing. 
     In other embodiments, a first user and a second user of a common (single) smart mirror in common (single) location can select a challenge workout (e.g., by interacting with a GUI of the first smart mirror or by interacting with a GUI of a first mobile compute device of the first user). In response to selecting the challenge workout, the smart mirror displays a challenge workout (e.g., selected by the first user and/or the second user, as part of the challenge workout selection). During the challenge workout, live video of the first user and the second user, obtained via one or more video cameras of the smart mirror, is displayed via the smart mirror display panel. 
     In other embodiments, a user of a smart mirror in a given location can select a challenge workout (e.g., by interacting with a GUI of the smart mirror or by interacting with a GUI of a mobile compute device of the user), where the challenge workout includes a previously-recorded video of the user performing a desired workout (and, optionally, including an overlay of numeric and/or non-numeric scores calculated at the time of the previous recording). In response to selecting the challenge workout, the smart mirror displays (“replays”) the challenge workout, such that the user can “face off” against his/her own previous performance of the workout. During the challenge workout, live video of the user, obtained via one or more video cameras of the smart mirror, is displayed via the smart mirror display panel, along with the challenge workout (with optional score overlay(s)) and, optionally, with an additional overlay of numeric and/or non-numeric scores based on the user&#39;s performance during the replay of the challenge workout. For example, in some such embodiments, the user can view both his/her score(s) from the previously-recorded video and his/her score(s) calculated during the replay, so that he/she can compare them and be motivated by them. The score(s) may change over time, throughout the duration of the challenge workout. In some embodiments, rather than displaying the scores from the previously-recorded video and the scores calculated during the replay individually, a numeric or non-numeric representation of the difference between the scores from the previously-recorded video and the scores calculated during the replay may be generated and displayed (e.g., a graphic, such as a thermometer, that shows a user (for example, via a color of the graphic, a length of the graphic, etc.) whether he/she is performing better or worse than he/she did during the previously-recorded workout, at any given time). In other words, the graphic can represent the user&#39;s “relative” performance, as compared with the previously-recorded workout. 
     In still other embodiments, a first user of a first smart mirror in a first location and a second user of a second smart mirror in a second location (the second smart mirror being different from the first smart mirror and the first location being different from the second location) can be selected automatically (referred to herein as a “face-off pairing”), by the app, based on a competitive compatibility score generated using a competitive compatibility algorithm. The competitive compatibility algorithm can use some or all of the following data to determine face-off pairings: historical biometric data, current biometric data, historical sensor data, current sensor data, historical workouts, historical workout performance, current workout and exercise, user preferences, and user demographics. Upon automatic selection of a face-off pairing, the app can send challenge requests to the smart mirror(s) of the first user and the second user, for display via a GUI thereof, such that the first user and the second user can accept or deny the challenge request. If both the first user and the second user (if associated with different smart mirrors in different locations) or one of the first user or the second user (if associated with the same common smart mirror) accept the challenge request, a challenge workout (e.g., selected by the app, optionally also based on the competitive compatibility algorithm) is displayed, via both smart mirrors simultaneously, or via the common smart mirror, respectively. 
     In some embodiments, the app uses AI to automatically identify face-off pairings that are predicted to promote increased future user engagement. For example, AI can be used to target predefined outcomes, by selecting a specified user having a higher predicted likelihood of winning certain challenges, and/or by selecting a specified user having a higher predicted likelihood of losing certain challenges. In some such embodiments, AI may select face-off pairings such that a user that has been exercising less frequently is predicted to lose automatically identified face-off pairings more frequently, and/or such that a user that has been exercising more frequently is predicted to win automatically identified face-off pairings more frequently. 
     In some embodiments, a networked plurality of smart mirrors can be configured (e.g., via a shared app, optionally also running on one or more mobile compute devices of users of the smart mirrors) to host a ladder tournament competition including a plurality of face-off pairings. Each face-off pairing can be broadcast via the networked plurality of smart mirrors to spectator users, participant users, and/or competitor users within the tournament (e.g., who have signed up for the tournament via the app). The app can automatically update a user listing within a ladder (which may be displayed in each mirror of the networked plurality of mirrors) in real-time or at a various times as the ladder tournament progresses. 
     In some embodiments, face-off pairings can be between two “teams” of smart mirror users, with each team including two or more competitors. During the face-off workouts, each team member within a given face-off pairing can view, via his/her smart mirror, the video and/or performance metrics (e.g., scores) of the other three team members, as well as the current point totals for each team. The teams can compete with each other in parallel or in series. 
     In some embodiments, face-off pairings of individual users can be implemented in a “tag team” format, such that a first user competes with a second user one-on-one, and when one of the users (e.g., the second user) tires out, a third user (e.g., viewing the face-off workout) can “tag” in and take the place of the second user, to continue the tag team face-off workout (with the third user&#39;s being captured by the smart mirror of the third user and displayed via the smart mirror of the first user) in a continuous manner. Similarly, face-off pairings of individual users can be implemented in a “relay race” format, such that a first user competes with a second user one-on-one, and when each of the first user and the second user reaches a particular/predetermined stage (e.g., distance, time, etc.), a third user and a fourth user, take over for the first user and the second user, respectively, to continue the relay face-off workout in a continuous manner. 
     In-Workout Spotlights: 
     In some embodiments, a plurality of users, each with his/her own smart mirror, participates, in parallel, in a common workout presented via their smart mirrors. During the workout, a “spotlight” display (e.g., including text, graphics, images and/or animation) can be applied to or associated with one or more selected users, and the spotlight display can be presented (e.g., as an overlay on a representation of the selected user(s)), via the smart mirrors of the participant users. The spotlight display can be transient (e.g., configured to be displayed for a predetermined period of time). The user(s) selected to be “spotlighted” can be selected automatically (e.g., by the app, using an algorithm, rule(s) and/or schedule) or can be selected by one or more of the participant users. For example, a user who is celebrating a birthday on the day of the workout can be automatically chosen for a spotlight, in response to determining (e.g., based on a calendar) that it is his/her birthday. 
     In some embodiments, a spotlight display is generated, selected and/or displayed (e.g., by a smart mirror, an app running on the smart mirror, a remote server communicably coupled to the smart mirror, a mobile compute device communicably coupled to the smart mirror, and/or an app running on the mobile compute device) using one or more AI algorithms. For example, an AI algorithm can identify, e.g., based on biometric data of one or more users from the plurality of users collected within a predefined period of time, one or more users from the plurality of users that are determined to need, or to be most in need of, encouragement, inspiration, or motivation (e.g., based on a detected decline in intensity, power, etc.). In some such embodiments, where more than a predetermined threshold number of users from the plurality of users are identified as needing encouragement, the AI algorithm and/or the app can down-select a subgroup of users from those identified as needing encouragement, such that spotlight displays are only displayed for those users within the subgroup (e.g., to avoid visually crowding/overwhelming the display, diluting the message, etc.). Similarly and more generally, in other embodiments, where more than a predetermined threshold number of users from the plurality of users are identified as candidates to be “spotlighted,” for example because they have birthdays or anniversaries, the AI algorithm and/or the app can down-select a subgroup of users from those candidates, such that spotlight displays are only displayed for those users within the subgroup (e.g., to avoid visually crowding/overwhelming the display, diluting the message, etc.). 
     Friending 
     In some embodiments, a first user of a first smart mirror can “invite” at least a second user of a second smart mirror to become a friend via a “double-opt-in” process (i.e., both the first user and the second user agree to friend each other). A number of “friends” of the first user who have previously completed a workout or attended a class, or who are actively participating in an ongoing instance of the workout, may be displayed and/or highlighted (optionally with prioritization) within the GUI of the given user&#39;s smart mirror during the workout or prior to the workout. Alternatively or in addition, live video of one or more friends of the first user may be displayed and/or highlighted (optionally with prioritization) during the workout, and/or icons, images, text, or other representations of the one or more friends of the first user may be displayed and/or highlighted (optionally with prioritization) during the workout. 
     In some embodiments, a smart mirror of a first user displays (e.g., during a workout) an activity feed that is viewable by the first user and, optionally, by friends of the first user (e.g., via their respective smart mirror). The activity feed can include data associated with the first user and with friends of the first user, including (but not limited to) one or more of: name, username, location, online status, workout log, biometric data (e.g., heart rate data), images, videos, accomplishments, milestones, etc. A first user may interact with an activity feed of a friended user, e.g., by posting text, emojis, videos, images, etc. in the activity feed. 
     In some embodiments, a smart mirror of a first user displays (e.g., during a workout) a leaderboard of all friended users, a subset of friended users, or users from the entire networked smart mirror community. Positioning of users within the leaderboard can be based on any or all of the following metrics: workouts completed, biometric data (e.g., heart rate data), points earned during competitive (e.g., “challenge”) workouts, and values calculated based on the foregoing data (e.g., most improved user(s)). The leaderboard can include a “podium” section (e.g., at the top of the leaderboard) that includes a predefined number (e.g., two, three, four, or five) of the highest-ranked users. 
     Trending Workouts 
     In some embodiments, workouts that are “trending” in a predefined community or subset of the community (e.g., a subset of the community that includes users similar to a first user) can be displayed via a smart mirror to the first user. As used herein, “trending” can refer to the condition of having a high overall rating, a high recent rating (e.g., within a predefined preceding period of time), a high overall usage, a high recent usage (e.g., within a predefined preceding period of time), etc. Trends can be defined and/or identified using one or more AI algorithms. For example, AI can be used to determine a desirable time window over which to identify trends (e.g., day, week, month, season) and/or a desirable geographic region within which to identify trends (e.g., country, state, county, city) and/or a desirable subset of users among which to identify trends (e.g., demographics, fitness level, workout frequency, user preferences, user settings, friends, etc.), such that a predicted level of user engagement resulting from the trending displays is higher/highest. Trends can be associated with a particular exercise type (e.g., yoga, running, boxing). 
     Milestones 
     In some embodiments, a plurality of users, each with his/her own smart mirror, participates, in parallel, in a common workout presented via their smart mirrors. During, before and/or after the workout, one or more “milestones” (e.g., notable events) can be displayed or otherwise presented via one or more smart mirrors (e.g., as text, audio, video, graphics, images, GIFs, etc.). A milestone can be identified (e.g., by a server, by one or more of the smart mirrors, an app running on one or more of the smart mirrors and/or an app running on one or more mobile compute devices) based, for example, on one or more of: class performance (e.g., based on data gathered during a workout, such as video data and biometric data), exercise performance (e.g., based on data gathered while performing the exercise, such as video data and biometric data), class attendance, performance across workouts (e.g., based on data gathered during a workout, such as video data and biometric data), calendar events (e.g., anniversary of signing up via the smart mirror, birthday, friend anniversaries), and smart mirror community or social interactions. Milestones can be displayed according to a predefined schedule, and thus may expected by the user(s). Alternatively, milestones can be surprise and/or unexpected achievements, such that the user(s) are not expecting to see them. AI can be used to determine one of the following, with regard to milestones: time(s)/date(s) for presenting surprise achievement milestones having the highest predicted likelihood of promoting/triggering future user engagement, types of surprise achievement milestones predicted to “delight” or be welcomed by a particular user, timing of the presentation of surprise achievement milestones during a workout, such that the user has a favorable response (rather than a negative response) to the milestone, a maximum frequency at which milestones may be displayed, such that a predicted likelihood of promoting/triggering future user engagement is highest, etc. 
     Virtual “Locker Room” Sessions 
     In some embodiments, a smart mirror app is configured to simulate an interactive “locker room” environment before and/or after a workout.  FIG.  4    is a diagram showing an example locker room implementation, in accordance with some embodiments. As shown in  FIG.  4   , during a first time interval (Time Interval 1—first virtual locker room), users A, E, and F are active (e.g., they are in front of their respective smart mirrors, optionally with their video cameras on, or have their app open on their mobile compute device(s)). At least a subset of the users A, E, and F may plan to participate in a common scheduled workout (which can be either a “live” workout or an “encore” workout). The first time interval precedes the time at which the workout is scheduled to begin. During the first time interval, the users A, E, and F can see and communicate with each other via voice, video, and/or chat (e.g., including text, image, emojis, GIFs (e.g., virtual towel snap GIF), etc.). Also during the first time interval, one or more user-selected backgrounds (e.g., images uploaded by each user or by a user that organized the workout) and/or images selected by the smart mirror app (e.g., according to one or more predefined rules and/or algorithms) can be displayed within the smart mirror of each of users A, E, and F. Images selected by the smart mirror app can include, for example, images of products for promotion and/or images depicting the rendering of services for promotion. The selection of images of products for promotion and/or images depicting the rendering of services for promotion can be based on one or more rules and/or algorithms based, for example, on user demographics, user preferences, user location data, user purchase history, etc. From the point of view of, for example, user A, other active users E and F can be “seen” via live video stream and/or via other representations, such as avatars, images, text, etc. In some embodiments, the visual/displayed appearance (e.g., including the background) of the first virtual locker room automatically changes as different users talk (e.g., concurrent with the current speaker being featured/enlarged within the viewable area). In some embodiments, an animation is displayed, to participants of the first virtual locker room and during the first time interval, of people getting ready for a workout (e.g., putting on shoes, warming up, etc.). 
     During a second time interval (Time Interval 2—scheduled workout), an instructor  401  and users A, B, C, and F are active (e.g., they are in front of their respective smart mirrors, optionally with their video cameras on). During a third time interval (Time Interval 3—second virtual locker room), users D, B, and F are active (e.g., they are in front of their respective smart mirrors, optionally with their video cameras on, or have their app open on their mobile compute device(s)). Users B and F participated in the preceding workout (during the second time interval), whereas user D did not. During the third time interval (similar to during the first time interval), the users B, D, and F can see and communicate with each other via voice, video, and/or chat (e.g., including text, image, emojis, GIFs (e.g., virtual towel snap GIF), etc.). Also during the third time interval, a user-selected background (e.g., an image uploaded by each user) can be displayed within the smart mirror of each of users A, E, and F. From the point of view of, for example, user B, other active users D and F can be “seen” via live video stream and/or via other representations, such as avatars, images, text, etc. In some embodiments, the visual/displayed appearance (e.g., including the background) of the first virtual locker room automatically changes as different users talk (e.g., concurrent with the current speaker being featured/enlarged within the viewable area). In some embodiments, an animation is displayed, to participants of the second virtual locker room and during the third time interval, of people doing post-workout activities (e.g., taking off shoes, cooling down, etc.). 
     In some embodiments, during the first virtual locker room and/or the second virtual locker room, the smart mirror displays of all participants are synchronized such that they display the same events occurring at the same time (e.g., users entering and exiting the virtual locker room), For example, if three users are in the virtual locker room, and a fourth user enters the locker room, the three users can simultaneously view that fourth user entering. As the fourth user enters, he/she sees the three friends already there in the virtual locker room. 
     Biometric Connector Systems 
     In some embodiments, a biometric “connector” apparatus is sized and shaped to connect to, attach to, or be embedded within, at least one of exercise equipment, apparel, footwear (e.g., one shoe or both shoes), or the body of a user, and contains a microcontroller communicably coupled to a plurality of sensors (optionally including at least one “onboard” sensor). The plurality of sensors includes sensors for detecting data that directly measures, or is used in the calculation of, one or more of the following non-exhaustive list of biometric data: position (e.g., via a global positioning system (GPS) sensor, altimeter, etc.), orientation or rotation (e.g., via a gyroscope, magnetometer, etc.), acceleration (e.g., via 3-axis accelerometer(s)), speed/velocity (e.g., limb speed, running speed, etc.), cadence, pace, gait, vibration, muscle activation (i.e., which muscle(s) are being activated, and to what degree) (e.g., using a stretch sensor, vibration sensor, etc.), temperature, humidity, oxygen levels (e.g., blood oxygen level, blood oxygen saturation, etc.), salinity, breathing rate, heart rate (e.g. via a bioimpedance sensor, optical sensor, photoplethysmography (PPS) sensor, etc.), muscle twitch response, heart rate recovery, perspiration rate, intensity, linear force, linear movement, rotational force, rotational movement, power (e.g., running power), repetition counts such as steps (e.g., via a pedometer), range of motion, movement patterns/trajectories, gestures, facial features (e.g., via facial recognition sensors), flexibility, endurance, strength, body fat, and hydration level. A biometric connector apparatus can include a connected weight (or “smart weight”), such as the connected weight  610  of  FIG.  6    or the connected weight dumbbell shown in  FIG.  7   , discussed below. 
     In some embodiments, a biometric connector system includes one or more biometric connector sensors, each configured to communicate (e.g., via Bluetooth® or other wireless network communications protocol) with one or more smart mirrors. During use (e.g., during a workout), the biometric connector sensor(s) detect biometric data for a user performing the workout, optionally store the biometric data locally (within the biometric connector sensor(s)), and generate and transmit signals representing the biometric data to the smart mirror (and/or to an app running on the smart mirror, and/or to a mobile compute device of the user). Once received, one or more of the following actions can be performed: the biometric data can be stored in memory, a representation of the biometric data (e.g., in text, graphic, and/or audio form) can be presented to the user via the smart mirror and/or via the mobile compute device), an alert can be generated based on the biometric data and presented to the user (e.g., in text, graphic, and/or audio form) via the smart mirror and/or via the mobile compute device), one or more recommendations (e.g., to correct form, to reduce intensity, to begin cool down, to increase intensity, to hydrate, to change to a different workout, etc.) can be generated based on the biometric data (e.g., according to one or more predetermined rules and/or based on one or more algorithms) and presented to the user (e.g., in text, graphic, and/or audio form) via the smart mirror and/or via the mobile compute device), etc. 
     In some embodiments, a biometric connector system includes one or more biometric connector sensors, each configured to communicate (e.g., via Bluetooth® or other wireless network communications protocol) with one or more smart mirrors (and/or with any other wall-mounted or freestanding appliance (including, but not limited to, other types of exercise equipment) having a display monitor/screen). During use (e.g., during a workout), the biometric connector sensor(s) detect biometric data for a user performing the workout, optionally store the biometric data locally (within the biometric connector sensor(s)), transform (e.g., via a microcontroller or processor thereof) the biometric data based on one or more algorithms to produce transformed biometric data (optionally having a non-numeric format, such as a graphical representation(s), sound(s) of varying intensity, color(s) of varying intensity, vibration(s) of varying intensity, or other sensory output(s)), and generate and transmit signals representing the transformed biometric data to the smart mirror (and/or an app running on the smart mirror, and/or a mobile compute device of the user) for presentation. The one or more algorithms can include one or more of: machine learning algorithms, statistical algorithms, unit conversion algorithms, biometric algorithms, encryption algorithms, and data compression algorithms. The transformed biometric data can include one or more of: compressed data, encrypted data, converted data, and modified data. Once received, one or more of the following actions can be performed: the transformed biometric data can be stored in memory, a representation of the transformed biometric data (e.g., in text, graphic, and/or audio form) can be presented to the user via the smart mirror and/or via the mobile compute device), an alert can be generated based on the transformed biometric data and presented to the user (e.g., in text, graphic, and/or audio form) via the smart mirror and/or via the mobile compute device, one or more recommendations (e.g., to correct form, to reduce intensity, to begin cool down, to increase intensity, to hydrate, to change to a different workout, etc.) can be generated based on the transformed biometric data (e.g., according to one or more predetermined rules and/or based on one or more algorithms) and presented to the user (e.g., in text, graphic, and/or audio form) via the smart mirror and/or via the mobile compute device), etc. 
     In some embodiments, a biometric connector system includes multiple biometric connector sensors, each configured to communicate (e.g., via Bluetooth® or other wireless network communications protocol) with one or more smart mirrors (and/or with any other wall-mounted or freestanding appliance (including, but not limited to, other types of exercise equipment) having a display monitor/screen). At least one biometric connector sensor from the multiple biometric connector sensors is attached to, embedded in, or otherwise associated with another type of exercise equipment, such as a treadmill, elliptical trainer, stationary bicycle, stair-stepper, rowing machine, cross-country ski machine, etc. The one or more smart mirrors (and/or an app running on the smart mirror(s), and/or mobile compute device(s) of the user(s)), upon receipt of biometric data from the other exercise equipment, may detect a type of exercise equipment associated with the biometric data, and select an algorithm and/or rule set for interpreting the biometric data based on the detected type of exercise equipment. 
     In addition to, or alternatively to, the sensors and detection techniques described herein, vibration, muscle activation, and other biometric data can be generated by one or more sensors and/or techniques described in U.S. Pat. No. 8,912,909, issued Dec. 16, 2014 and titled “Noninvasive Multi-Parameter Patient Monitor”; U.S. Patent Application Publication Number 2018/0271409, published Sep. 27, 2018 and titled “Body Part Motion Analysis with Wearable Sensors”; and U.S. Patent Application Publication Number 2019/0022388, published Jan. 24, 2019 and titled “Device and System to Measure and Assess Superficial Muscle Contractile Characteristics,” the entire contents of each of which are herein incorporated by reference in their entireties for all purposes. 
     In some embodiments, biometric data is gathered, over time, from each of a plurality of networked smart mirrors (and/or from any other wall-mounted or freestanding appliance (including, but not limited to, other types of exercise equipment) having a display monitor/screen) and for each of a plurality of smart mirror users, and stored in a centralized repository (e.g., a cloud server). One or more machine learning models can be trained using the stored biometric data, to produce one or more trained machine learning models. The one or more trained machine learning models can detect, optionally adaptively over time (by retraining the one or more trained machine learning models based on additional biometric data gathered since the previous machine learning training), trends among subgroups of smart mirror users, such as: workout popularity, low performance statistics for individual workouts, high performance statistics for individual workouts, high interaction with other users during certain time periods, high interaction with other users during certain workouts, high interaction with other users on certain days, high interaction with other users for certain instructors, etc. 
     In some embodiments, biometric data is gathered, over time, from each of a plurality of networked smart mirrors (and/or from any other wall-mounted or freestanding appliance (including, but not limited to, other types of exercise equipment) having a display monitor/screen) and for each of a plurality of smart mirror users, and stored in a centralized repository (e.g., a cloud server). One or more machine learning models can be trained using a subset of the stored biometric data, the subset of the stored biometric data being selected based on one or more properties of a given user (e.g., biometric data, age, gender, height, weight, workout preferences, past workout performance, fitness level, etc.) to produce one or more trained machine learning models. The one or more trained machine learning models can then generate, optionally adaptively over time (by retraining the one or more trained machine learning models based on additional biometric data gathered since the previous machine learning training), recommendations for the user, including one or more of (but not limited to): 
     recommended modifications to form (e.g., body positioning), workout recommendations, instructor recommendations, “friend” (i.e., other smart mirror user) recommendations, etc. The recommendations can also be based, in part, on one or more predefined user-customizable goals. For example, the trained machine learning model(s) can generate recommendations that are predicted to result in the user moving closer to his/her goal(s). Examples of user-customizable goals can include metrics such as (but not limited to): fitness level, mastery score (discussed further below), sport-specific fitness level (e.g., specific to yoga, running, calisthenics, cycling, biometric data (e.g., during the performance of one or more specified workouts), sport-specific form, sport-specific performance, workout-specific form, workout-specific performance, exercise-specific form, or exercise-specific performance. In some implementations, a first user can customize his/her goals by inputting (via a GUI of the smart mirror or mobile compute device) a name or identifier of one or more other smart mirror users, along with the metric(s) of that other smart mirror user that the first user would like to attain or progress toward. 
     In some embodiments, a biometric connector system includes one or more “connected weights.” As used herein, a connected weight can refer to exercise equipment that (1) includes or is combined with one or more sensors, and (2) is configured to communicate with one or more smart mirrors and/or compute devices (e.g., to transmit/send sensor data generated by the one or more sensors). The communication can be via Bluetooth® or any other wireless network communications protocol. The one or more sensors (and, optionally, additional electronics such as a power supply, a transceiver, a transmitter, an antenna, a processor (e.g., a microprocessor), and/or a memory) can include one or more sensors positioned within the exercise equipment (e.g., within an external housing, coating (e.g., neoprene or rubber), or layer thereof), one or more sensors positioned on or around at least an exterior portion of the exercise equipment (e.g., mechanically clamped thereto, adhered thereto via an adhesive, secured thereto using a fastener such as a hook-and-loop fastener, engaged therewith via a screw-thread engagement, connected thereto via a friction fit fastener, etc.), and/or one or more sensors that are embedded in or formed integrally with the external housing, coating, or layer of the exercise equipment. The one or more sensors and optional electronics can be co-located within a housing or on a common substrate of the exercise equipment, and the sensors, optional electronics, and housing or substrate can collectively be referred to as a “connector sensor” (the term “connector” referring to the wireless communication connectivity established between the connected weight and the one or more smart mirrors and/or compute devices with which the connected weight can communicate). The connector sensor can have a form factor such that it is readily coupled to exercise equipment. For example, in some embodiments, a connector sensor includes a housing having an actuator (e.g., a spring-loaded button) and having an inner surface (e.g., a threaded inner surface). The housing is configured to mechanically couple, via the inner surface, to a complementary outer surface (e.g., a threaded outer surface) of a dumbbell. The complementary outer surface of the dumbbell can be positioned, for example, on a handle/bar of the dumbbell. The connector sensor also includes at least one power supply disposed within the housing, and at least one sensor, a processor, and a transceiver, each disposed within the housing and electrically coupled to the power supply. The processor is configured to receive a first signal representing signal data from the at least one sensor when the housing is mechanically coupled to the dumbbell, and to cause the transceiver to transmit a second signal representing the signal data to a smart mirror. 
     Exercise equipment can include any apparatus or device that can be used during physical activity to enhance the strength or conditioning effects of that physical activity. Examples of exercise equipment suitable for use as part of a connected weight include, but are not limited to, free weights such as dumbbells (e.g., hex head dumbbells, rubber dumbbells, urethane dumbbells, chrome dumbbells, spin-lock dumbbells, etc.), kettlebells, barbells, long bars, curl bars, angle weights, collars, tricep bars, hexagon-shaped bars, weight plates, cables and/or resistance bands. 
     In some embodiments, a connected weight includes a dumbbell, barbell, or other exercise equipment, and a connector sensor (e.g., sized and shaped as an easy-slide nut, discussed below) that is attached to the dumbbell, barbell, or other exercise equipment. The connector sensor includes one or more sensors. The one or more sensors include one or more of: a sensor configured to detect position and orientation (e.g., a gyroscope or magnetometer), a sensor configured to detect position (e.g., a GPS sensor or an altimeter), a sensor configured to detect orientation, a sensor configured to detect acceleration and velocity (e.g., an accelerometer, such as a  3 -axis accelerometer), a sensor configured to detect acceleration, a sensor configured to detect speed/velocity, a sensor configured to detect cadence, a sensor configured to detect vibration, a sensor configured to detect muscle activation (e.g., a stretch sensor or a vibration sensor), a sensor configured to detect temperature, a sensor configured to detect humidity, a sensor configured to detect oxygen level(s) (e.g., blood oxygen level(s)), a sensor configured to detect blood oxygen saturation, a sensor configured to detect salinity, a sensor configured to detect breathing rate, a sensor configured to detect heart rate (e.g. a bioimpedance sensor, an optical sensor, a PPS sensor, etc.), or any other sensor described herein. The connector sensor also optionally includes one or more of: a power supply, a transceiver, a transmitter, an antenna, a processor (e.g., a microprocessor), or a memory. The connector sensor can include a housing within which the one or more sensors, the power supply, the transceiver, the transmitter, the antenna, the processor, or the memory are positioned. 
     In some embodiments, a connected weight includes a dumbbell or other exercise equipment and one or more sensors that are embedded within and contained within the exercise equipment. In addition to the one or more sensors, the connected weight also optionally includes, embedded therein or contained therewithin, one or more of: a power supply, a transceiver, a transmitter, an antenna, a processor (e.g., a microprocessor), or a memory. 
     In some embodiments, a connected weight includes a dumbbell and a connector sensor that is configured as an “easy-slide nut,” as shown in  FIGS.  6 - 7   . For example,  FIG.  6    is a rendering of a connected weight  610  including a dumbbell  611  and a connector sensor  612  configured as an easy-slide nut (or locking nut). The dumbbell  611  includes a handle or bar  611 A and plurality of weighted plates  611 B- 611 D. In some embodiments, the dumbbell  611  is an adjustable dumbbell, and during assembly of the connected weight  610 , the weighted plates  611 B- 611 D (i.e., a first set of weighted plates) are slid onto a first end of the handle/bar  611 A, followed by the locking nut  612 , which can be used to secure the weighted plates  611 B- 611 D to the handle/bar  611 A and prevent their movement along the handle/bar  611 A during exercise. Also during assembly, a similar set of weighted plates (i.e., a second set of weighted plates) is slid onto a second end of the handle/bar  611 A, the second end of the handle/bar  611 A being opposite the first end of the handle/bar  611 A. The second set of weighted plates may be secured by a non-functionalized nut or clamp (i.e., having no sensor or communication functionality) or by a second connector sensor (optionally also configured as a locking nut). During disassembly, the weighted plates  611 B- 611 D can be removed from the handle/bar  611 A by first removing the locking nut  612  from the handle/bar  611 A and then sliding the weighted plates  611 B- 611 D off the handle/bar  611 A. In other embodiments, the dumbbell  611  is a non-adjustable dumbbell (i.e., including weighted plates that are integrally formed with, or otherwise permanently secured to, a handle/bar thereof), and a connector sensor is positioned at one or both ends thereof, for purposes of sensing but not to mechanically secure the weighted plates in place. In some such embodiments, a connector sensor is positioned at one end of the non-adjustable dumbbell and a non-functionalized nut or clamp at an opposite end of the non-adjustable dumbbell. 
     The locking nut connector sensor  612  includes a body portion  612 A, an endcap portion  612 B, and a spring-loaded button  612 C. The body portion  612 A and the endcap portion  612 B may be distinct (e.g., separately formed) components that are configured to be mechanically coupled to one another (e.g., via press-fit, screw-thread engagement, etc.) or adhesively coupled to one another, or may be monolithically formed as a single component. In some embodiments, the locking nut connector sensor  612  includes a threaded internal surface configured to mechanically engage with a threaded surface of the handle/bar  611 A. During installation of such a locking nut connector sensor  612  (e.g., after one or more of the weighted plates  611 B- 611 D has been positioned on the handle/bar  611 A), a user can depress the spring-loaded button  612 C to cause the threads of the threaded internal surface of the locking nut connector sensor  612  to shift/move in an outward direction (e.g., radially away from a central longitudinal axis of the locking nut connector sensor  612 ). While the spring-loaded button  612 C is depressed, the user can freely slide the locking nut connector sensor  612  along the handle/bar  611 A to a desired position without the threaded internal surface of the locking nut connector sensor  612  engaging with the threaded surface of the handle/bar  611 A. Once the user has positioned the locking nut connector sensor  612  at the desired position along the handle/bar  611 A, the user can release the spring-loaded button  612 C to cause the threads of the threaded internal surface of the locking nut connector sensor  612  to shift/move in an onward direction (e.g., radially toward the central longitudinal axis of the locking nut connector sensor  612 ) such that the threaded internal surface of the locking nut connector sensor  612  engages with the threaded surface of the handle/bar  611 A. In some embodiments, the locking nut connector sensor  612 , once engaged with the threaded surface of the handle/bar  611 A, can be tightened about the handle/bar  611 A (e.g., via manual rotation by the user) until a locked configuration is achieved. The locked configuration can refer to a desired amount of “tightness” (e.g., hand-tight), or can refer to configuration in which an amount of force between the threaded internal surface of the locking nut connector sensor  612  and the threaded surface of the handle/bar  611 A. The locking nut connector sensor  612  can be configured to provide, during tightening, an indication (e.g., an audible or haptic click) that the locked configuration has been reached. 
     In some embodiments, the locking nut connector sensor  612  is configured to provide feedback to the user, for example in the form of an audible sound, a visible indication (such as a light or video display), and/or haptic feedback. When the feedback is audible or haptic, it can be through the same mechanism as in the locking nut connector sensor  612 , or a different/distinct component. The feedback can be provided in response to detecting a condition, for example, that a form, movement, or action of the user when performing exercise is incorrect, undesirable, or dangerous (e.g., lifting movement is too fast, lowering movement is too fast, an incorrect grip on the connected weight  610 , movement with the wrong positioning or trajectory, etc.). An undesirable form, movement, or action can be detected using one or more sensors (e.g., pressure sensors, accelerometers, etc.) and can be based on one or more predefined rules, which may include user-defined or user-reconfigurable rules. The detecting of the condition, the selection or generation of the feedback, and the providing of the feedback can be performed within the locking nut connector sensor  612  alone, within one or more smart mirror(s) that receive data from the locking nut connector sensor  612  alone, or within both the locking nut connector sensor  612  and the one or more smart mirror(s). 
     In some embodiments, a locking nut is non-functionalized (i.e., does not include any sensors or electronics), but functions mechanically in a manner similar to that described above. In other words, the non-functionalized locking nut can include a body portion, an endcap portion, and a spring-loaded button. The body portion and the endcap portion may be distinct (e.g., separately formed) components that are configured to be mechanically coupled to one another (e.g., via press-fit, screw-thread engagement, etc.) or adhesively coupled to one another, or may be monolithically formed as a single component. In some embodiments, the non-functionalized locking nut includes a threaded internal surface configured to mechanically engage with a threaded surface of a handle/bar. During installation of such a non-functionalized locking nut (e.g., after one or more weighted plates has been positioned on the handle/bar), a user can depress the spring-loaded button to cause the threads of the threaded internal surface of the non-functionalized locking nut to shift/move in an outward direction (e.g., radially away from a central longitudinal axis of the non-functionalized locking nut). While the spring-loaded button is depressed, the user can freely slide the non-functionalized locking nut along the handle/bar to a desired position without the threaded internal surface of the non-functionalized locking nut engaging with the threaded surface of the handle/bar. Once the user has positioned the non-functionalized locking nut at the desired position along the handle/bar, the user can release the spring-loaded button to cause the threads of the threaded internal surface of the non-functionalized locking nut to shift/move in an onward direction (e.g., radially toward the central longitudinal axis of the non-functionalized locking nut) such that the threaded internal surface of the non-functionalized locking nut engages with the threaded surface of the handle/bar. In some embodiments, the non-functionalized locking nut, once engaged with the threaded surface of the handle/bar, can be tightened about the handle/bar (e.g., via manual rotation by the user) until a locked configuration is achieved. The locked configuration can refer to a desired amount of “tightness” (e.g., hand-tight), or can refer to a configuration in which an amount of force between the threaded internal surface of the non-functionalized locking nut and the threaded surface of the handle/bar. The non-functionalized locking nut can be configured to provide, during tightening, an indication (e.g., an audible or haptic click) that the locked configuration has been reached. 
       FIG.  7    is a photographic image of a connected weight, including a dumbbell and a connector sensor, in accordance with some embodiments. As shown in  FIG.  7   , the connected weight dumbbell includes a handle/bar  711 A and a single weighted plate  711 B at a first end of the handle/bar  711 A. The single weighted plate  711 B is secured in place along the handle/bar  711 A by a locking nut connector sensor  712  (similar to the locking nut connector sensor  612  of  FIG.  6   ) having a body portion  712 A, an endcap portion  712 B, and a spring-loaded button  712 C. Another single weighted plate (not shown) is positioned at a second end of the handle/bar  711 A, the second end opposite the first end. 
     In some embodiments, a given connected weight of the present disclosure, such as the connected weight  610  of  FIG.  6    or the connected weight dumbbell shown in  FIG.  7   , is configured (e.g., has a size and shape) to be removably connected to, and is compatible with, multiple different types of exercise equipment (e.g., weights made by different manufacturers and/or having different physical characteristics). In other words, existing exercise equipment can be retrofit to include functionalities described herein by attaching one or more of the locking nut connector sensors to the exercise equipment. 
       FIG.  8    is a system diagram showing connected weights and smart mirrors, in accordance with some embodiments. As shown in  FIG.  8   , the system  800  includes a first connected weight  811 A and a second connected weight  811 B. The first connected weight  811 A may be in close proximity (e.g., within about 10 feet) of a first smart mirror  800 A and associated with a first user. The second connected weight  811 B may be in close proximity (e.g., within about 10 feet) of a second smart mirror  800 B and associated with a second user in a location different from a location of the first user. The first connected weight  811 A includes one or more first connector sensors  812 A each including one or more sensors  813 A, a transceiver  814 A, an optional processor  815 A, an optional memory  816 A, and an optional power supply  817 A. Similarly, the second connected weight  811 B includes one or more second connector sensors  812 B each including one or more sensors  813 B, a transceiver  814 B, an optional processor  815 B, an optional memory  816 B, and an optional power supply  817 B. In some implementations, one or more of the sensors  813 A and/or one or more of the sensors  813 B can include its own onboard power supply, processor, memory and/or transceiver, separate from the optional power supplies  817 A,  817 B, the optional processors  815 A,  815 B, the optional memories  816 A,  816 B, and the transceivers  814 A,  814 B. Each of the connected weights  811 A,  811 B can communicate (e.g., using the transceivers  812 A and  812 B, respectively) via a wireless communications network “N” with a remote compute device  820  and/or with the associated smart mirror (smart mirror  800 A and smart mirror  800 B, respectively), to send sensor data ( 830 A and  830 B, respectively) generated by the sensors  813 A,  813 B during exercise. As shown in  FIG.  8   , sensor data  830 A can be sent from the connector sensor(s)  812 A to the remote compute device  820  and/or to the smart mirror  800 A. Similarly, sensor data  830 B can be sent from the connector sensor(s)  812 B to the remote compute device  820  and/or to the smart mirror  800 B. Sensor data that is sent to the remote compute device  820  can be sent to the smart mirrors  800 A,  800 A. For example, sensor data  830 C can include sensor data  830 A, sensor data  830 B, or both. Similarly, for example, sensor data  830 D can include sensor data  830 A, sensor data  830 B, or both. The sensor data  830 C and/or the sensor data  830 D can include raw sensor data (i.e., data as received from the connected weight(s)  811 A,  811 B) and/or can include a modified version of the raw sensor data. For example, the sensor data  830 C and/or the sensor data  830 D can include normalized data, combined data, averaged data, etc. In some embodiments, the raw sensor data is modified based on an artificial intelligence (“AI”) algorithm (e.g., a regression-based AI algorithm, such as linear regression, support vector regression (“SVR”), regression trees, neural network regression, decision trees, LASSO regression, ridge regression, ElasticNet regression, etc.) and a pattern-matching detection technique can be used to determine a movement of the user(s) and/or a quality of a performance of the user(s). Optionally, the first smart mirror  800 A and the second smart mirror  800 B are configured to communicate with one another directly, for example to exchange sensor data  830 E about the first user and/or the second user. 
       FIGS.  9 A- 9 I  are diagrams of example connected weight configurations, in accordance with some embodiments.  FIG.  9 A  shows a connected weight including a dumbbell and a connector sensor  912 A positioned on or within a grip disposed on the handle/bar of the dumbbell.  FIG.  9 B  shows a connected weight including a dumbbell and a connector sensor  912 B positioned on or within a weight plate of the dumbbell.  FIG.  9 C  shows a connected weight including a dumbbell and connector sensors  912 C positioned on or within multiple weight plates of the dumbbell.  FIG.  9 D  shows a connected weight including a dumbbell and a connector sensor  912 D positioned on or within one handle/bar of the dumbbell. In some such embodiments, the connector sensor  912 D is positioned on a first handle of the dumbbell, and a “dumb” locking nut (i.e., a locking nut that does not include sensors, and thus is not “smart,” but still functions to secure a weight plate of the connected weight along the second handle) is positioned on a second handle of the dumbbell, the second handle opposite the first handle. The dumb locking nut may have substantially the same external appearance as the connector sensor  912 D, and/or may weigh substantially the same as the connector sensor  912 D. 
       FIG.  9 E  shows a connected weight including a dumbbell and connector sensors  912 E 1 ,  912 E 2  positioned on or within both ends of the handle/bar of the dumbbell.  FIG.  9 F  shows a connected weight including a dumbbell and a separate connector sensor  912 F positioned in close proximity to (e.g., within 10 feet or within 5 feet of) the dumbbell, for example on the user&#39;s body, clothing, or shoes. The separate connector sensor  912 F may include a camera configured to detect and optionally analyze a user&#39;s movements.  FIG.  9 G  shows a connected weight including a dumbbell and a connector sensor comprising a glove accessory  912 G positioned in close proximity to (e.g., within 10 feet or within 5 feet of) the dumbbell.  FIG.  9 H  shows a connected weight including a dumbbell with a first connector sensor  912 H 1  and a second connector sensor comprising a glove accessory  912 H 2  positioned in close proximity to (e.g., within 10 feet or within 5 feet of) the dumbbell. During exercise, a user wears the glove accessory  912 H 2 , and when gripping the dumbbell, an active portion of the glove accessory  912 H 2  contacts the first connector sensor  912 H 1 , for example such that biometric sensor data detected by the glove accessory can be transferred from the glove accessory to the first connector sensor  912 H 1 . 
       FIG.  9 I  shows a pair of dumbbells, one or both of which can be a connected weight. As shown in  FIG.  9 I , a first dumbbell from the pair of dumbbells can include a connector sensor  912 J 1  and/or a connector sensor  912 J 2 . Similarly, a second dumbbell from the pair of dumbbells can include a connector sensor  912 J 3  and/or a connector sensor  912 J 4 . Each of the optional connector sensors  912 J 1 ,  912 J 2 ,  912 J 3 , and  912 J 4  can be embedded within or contained within the dumbbell(s), within the bar region and/or the “head” region(s) thereof 
     During use by a user (e.g., during exercise) of any of the connected weights shown in  FIGS.  9 A- 91   , real-time data (e.g., similar to sensor data  830 A,  830 B of  FIG.  8   ), including raw data and/or modified data, can be transmitted from the connected weight(s) to one or more smart mirrors and/or remote compute devices (e.g., mobile devices such as smart phones) in communication (e.g., wireless network communication) with the connected weight(s). The real-time data can include, for example, repetition count(s), movement data (e.g., speed, velocity, direction, acceleration, position data, etc.). In response to, and based on, the real-time data, the one or more smart mirrors and/or the one or more remote compute devices can generate one or more messages for display to the user via the smart mirror(s) and/or the remote compute device(s). The one or more messages can include a text, graphic, video and/or audio representation of one or more of: repetition count(s), recommended weight modifications (e.g., a recommendation that the user use heavier weight(s) or lighter weight(s), which may or may not be connected weight(s)), or recommended form modifications (e.g., a recommendation that the user modify the way that the user is holding/gripping the connected weight(s), or a recommendation that the user modify a body positioning or stance). Generating the one or more messages can include the use of one or more AI algorithms. In some embodiments, the one or more smart mirrors and/or the one or more remote compute devices can use the real-time data to perform comparisons of users (thereby generating comparison data), and the one or more messages can include a representation of the comparison data or a representation of a user&#39;s relative performance as compared to one or more other specified users. 
     Biometric Connector Software 
     In some embodiments, a biometric connector system includes a connector software application having instructions to cause a processor to calculate a mastery score (or “fluidity score”) according to an algorithm. In one example, the mastery score is calculated based on a number of repetitions completed, one or more movement patterns, body positioning data (e.g., including coordinates within three-dimensional space and representations of associated body parts), muscle usage/activation data, cadence, and heart rate recovery data for a given user. In some such implementations, the algorithm combines calculated values (e.g., calculated based on data from one or more sensors) with raw sensor data to determine the mastery score. Once calculated, the mastery score can be presented to the user (e.g., in text, graphic, and/or audio form) via the smart mirror and/or via the mobile compute device of the user. The data from one or more sensors, the calculated values, and/or the raw sensor data can include data generated by and/or received from one or more connected weights (such as connected weight  610  of  FIG.  6   ). 
     In some embodiments, a biometric connector system includes a connector software application having instructions to cause a processor to capture video of a user completing exercises, during a first workout period, and stores that video as a first archive video (optionally associated, in memory, with one or more of: a timestamp, date stamp, and biometric data). During a second workout period subsequent to the first workout period, the connector software application can be configured to cause display, via the smart mirror, of an overlay of the first archive video, optionally in combination with the biometric data of the first archive video, such that the user can see his/her reflected image concurrently with the first archive video of himself/herself (e.g., for self-comparison, competition with one&#39;s own prior performance, etc.). In some embodiments, the overlay can include a visual representation of data collected via one or more connected weights during recording of the first archive video and/or one or more messages previously presented to a user during the recording of the first archive video and based on data generated by one or more connected weights at that time. The overlay can include a visual representation of a form correction, an incorrect form/movement, and/or one or more muscles that are expected to be activated during a given exercise depicted in the first archive video. 
     In some embodiments, a biometric connector system includes a connector software application having instructions to cause a processor to combine video camera data/imagery captured by a smart mirror of a user with biometric data generated based on one or more wearable electronic accessories of the user (optionally synchronized in time or matched based on time of capture/generation) to define composite data, and make determinations based on the composite data or based on the video camera data/imagery and the biometric data sequentially. For example, a movement (e.g., a vibration, shaking, contraction, etc.) of the user can be detected based on the video camera data/imagery, and biometric data (e.g., generated by a vibration sensor, stretch sensor and/or other sensor) can be used to confirm the movement and/or specify which muscle(s) are most exhibiting the movement, relative to other muscles of the user. Alternatively, the movement of the user can be detected based on the biometric data, and the video camera data/imagery can be used to confirm the movement and/or specify which muscle(s) are most exhibiting the movement, relative to other muscles of the user. In some such embodiments, the video camera data/imagery, the biometric data, and/or the composite data can be compared to one or more expected values associated with a workout being performed by the user, via the smart mirror, concurrently with the capture of the video camera data/imagery and the generation of the biometric data. Based on the comparison, the connector software application may determine whether a given exercise is (or was) being properly performed by the user, and/or to assess a form or other performance of the user. Optionally, the determination as to whether a given exercise is (or was) being properly performed by the user, and/or to assess a form or other performance of the user can be further based on audio data generated by one or more microphones of the smart mirror. 
     In some embodiments, optionally in combination with any of the preceding embodiments, biometric data can be used by the connector software application to calculate or infer a power (e.g., a running power) of a user during a workout. As used herein, “power” can refer to a user&#39;s ability to move weight with speed (also referred to as “explosiveness”). Power can be calculated, for example, using one or more techniques described in U.S. Pat. No. 10,744,371, issued Aug. 18, 2020 and titled “Methods and Apparatus for Power Expenditure and Technique Determination During Bipedal Motion,” and in U.S. Patent Application Publication Number 2017/0189752, published Jul. 6, 2017 and titled “Methods and Apparatus for Power Expenditure and Technique Determination During Bipedal Motion,” the entire contents of each of which are herein incorporated by reference in their entireties for all purposes. The connector software application can compare calculated power for a given time period and for a given user, with at least one other biometric data parameter, to confirm accuracy and/or to generate a more complete statistical profile of the user&#39;s performance during a given workout, sport, exercise, etc., which can be tracked over time.  FIG.  5    is a diagram showing an example of interrelatedness of certain biometric data parameters (namely, heart rate, rate of perceived exertion (RPE), pace, and power) for a user running uphill, downhill, and on flat terrain. As an example, referring to  FIG.  5   , in some embodiments, the connector software application can compare calculated power for a first time period, during which a user is running uphill and then transitions to running downhill, with a heart rate, pace, and/or RPE of the user for the same time period, to confirm that the measurements of the associated sensors are accurate. As shown in  FIG.  5   , if the sensors are performing correctly, the heart rate and RPE (for the first time period) should increase, plateau, and then decrease; the pace should increase when the user is running downhill, relative to when the user was running uphill; and the power should decrease when the user is running downhill, relative to when the user was running uphill (e.g., at a faster rate than the decrease(s) of RPE and/or heart rate during the downhill segment of the run). 
     Smart Dumbbells 
     In some embodiments, a smart dumbbell includes a first weight plate, a second weight plate, and an elongate, substantially cylindrical handle. The first weight plate assembly includes a first pair of endplates and a first over-molded weight. The second weight plate assembly includes a second pair of endplates and a second over-molded weight. The handle is mechanically coupled at a first end to the first weight plate assembly and at a second end to the second weight plate assembly. At least one of the first weight plate assembly or the second weight plate assembly includes at least one light-emitting diode (LED) and a transparent or translucent numerical indicator associated with a total weight of the apparatus and through which light emitted from the at least one LED is transmitted when the at least one LED is activated. 
       FIG.  10 A  is a diagram showing a perspective view of a smart dumbbell, in accordance with some embodiments. As shown in  FIG.  10 A , the smart dumbbell  1000  includes endplates  1014 , a handle  1001 , and over-molded weights  1007 . Each of the endplates  1014  includes a cutout region in the shape of a numeral, through which a transparent or translucent numerical indicator  1030  is visible (although in other implementations, only one (or two or three) of the endplates  1014  includes such a cutout region). The numerical indicator is associated with a total weight of the apparatus, and light emitted from the at least one LED is transmitted through the numerical indicator when the at least one LED is activated.  FIGS.  10 B- 10 C  are diagrams showing left and right views, respectively, of the smart dumbbell of  FIG.  10 A , and  FIG.  10 D  is a diagram showing a side view of the smart dumbbell of  FIG.  10 A . 
       FIG.  11    is a diagram showing an exploded view of a smart dumbbell, in accordance with some embodiments. As shown in  FIG.  11   , the smart dumbbell  1100  includes a handle  1101  (e.g., having a knurled surface), an inside endplate  1102  with a battery door/access defined therein and configured to accommodate a battery  3 , an inside endplate  1105  with a battery door/access defined therein (although in other implementations, the inside endplate  1105  may not include such a battery door/access), adhesive tapes (e.g., acrylic tape such as 3M™ VHB™ tape)  1116 ,  1117 ,  1118 , and  1119 , over-molded weights  1107 , fasteners (e.g., nuts)  1109 , fasteners  1113  (e.g., button head cap screws), printed circuit boards  1111  and  1120  (one or both of which includes one or more light-emitting diodes (LEDs)), a transparent or translucent numerical indicator  1110  (also referred to herein as a “light guide”), outer endplates  1114 , and tabs (or “pillars”)  1106  to fill in or serve as the center of the “0” in the numeral “20” depicted in endplates  1114  (e.g., secured using an adhesive tape or glue). A ribbon cable  1112  passes through a channel or cavity within the handle  1101  to provide electrical connectivity between components to the left of the handle  1101  in  FIG.  11    (i.e., inside endplate  1102 , fastener  1103 , adhesive tapes  1116 - 1119 , over-molded weight  1107 , fasteners  1109  and  1113 , printed circuit board  1120 , numerical indicator  1110 , tab  1106  and outer endplate  1114 ) and components to the right of the handle  111  in  FIG.  11     11  (i.e., inside endplate  1105 , adhesive tapes  1116 - 1119 , over-molded weight  1107 , fasteners  1109  and  1113 , printed circuit board  1111 , numerical indicator  1110 , tab  1106  and outer endplate  1114 ). 
     In some implementations, a majority of the weight/heft of the smart dumbbell resides in the over-molded weights  1107 . For example, as noted above, the numerical indicator can be associated with or represent a total weight of the apparatus, and up to about 70%, or up to about 75%, or up to about 80%, or up to about 85%, or up to about 90%, or up to about 95% of the total weight of the apparatus can reside in the over-molded weights  1107  (e.g., approximately half of the total weight residing in each of the first over-molded weight  1107  and the second over-molded weight  1107  from the pair of over-molded weights  1107 ). In other implementations (e.g., for smaller weights of 1 lb, 2 lb, 3 lb, 4 lb, or 5 lb), a majority of the weight/heft of the smart dumbbell can reside in the handle  1101 . 
     Each of the over-molded weights  1107  can include a substrate and an overmolding. The substrate can include one or more of: metal, metal alloy, ceramic, polymer, or composite. The overmolding can include one or more of: an elastomer (e.g., a rubber, such as cis-polyisoprene (natural rubber, NR), cis-polybutadiene (butadiene rubber, BR), styrene-butadiene rubber (SBR), and ethylene-propylene monomer (EPM), a silicone, or a plastic. The shape (i.e., height, weight, and/or thickness) and/or the weight of each the over-molded weights  1107  can be selected based on (1) whether a battery cavity is needed on the associated side of the smart dumbbell  1100 , and/or (2) a desired weight of the smart dumbbell  1100 . 
     The over-molded weights  1107  can include a peripheral/perimeter edge comprising a ridged, lightly-textured rubber. The ridged rubber border region of the over-molded weights  1107  can extend further outwardly from the smart dumbbell  1100  than other (e.g., metal) portions of the smart dumbbell  1100 , such that when the smart dumbbell  1100  is positioned on a surface (e.g., a gym rack, a table, the floor, etc.), a portion of the ridged rubber border region contacts the surface, as opposed to the other portions of the smart dumbbell  1100 . This facilitates reduced noise when setting the smart dumbbell  1100  down or when shifting multiple smart dumbbells  1100  so that they contact one another. The ridged rubber border region can also absorb shock and vibration during use, thereby preserving the structural integrity of the other portions/components of the smart dumbbell  1100 . 
     In some implementations, the smart dumbbell  1100  is semi-symmetrical, in that there is only a battery  1103  on one side of the handle  1101 . Components to the left of the handle  1101  in  FIG.  11    (i.e., inside endplate  1102 , fastener  1103 , adhesive tapes  1116 - 1119 , over-molded weight  1107 , fasteners  1109  and  1113 , printed circuit board  1120 , numerical indicator  1110 , tab  1106  and outer endplate  1114 ) can be referred to as a “primary side” of the smart dumbbell  1100 , and the printed circuit board  1120  can be referred to as a “primary board.”Components to the right of the handle  1101  in  FIG.  11    (i.e., inside endplate  1105 , adhesive tapes  1116 - 1119 , over-molded weight  1107 , fasteners  1109  and  1113 , printed circuit board  1111 , numerical indicator  1110 , tab  1106  and outer endplate  1114 ) can be referred to as a “secondary side” of the smart dumbbell  1100 . The primary side can be configured to supply the main power, and to send/transmit power to the secondary side via the ribbon cable  1112  passing through the handle. In some implementations, however (e.g., in 1 lb and 3 lb smart dumbbell configurations), the one or more LEDs are included only one side of the handle  1101 , and there is no electrical connection between the two sides (i.e., the ribbon cable  1112  is not included). 
     In some implementations, each of the endplates  1102 ,  1105 , and  1114  is a zinc (Zn) die-cast endplate. 
     In some implementations, the smart dumbbell  1100  is configured to illuminate the one or more LEDs behind the numerical indicator  1110  as an indication of an effort being expended by a user of the smart dumbbell  1100  (e.g., emitting blue or green light to indicate light effort/low intensity, and/or emitting red or orange light to indicate heavy effort/high intensity) and/or as an indication of a battery level of the smart dumbbell  1100 . 
     In some implementations, the “M” insignia shown in  FIG.  11    is printed, painted, or adhered on an outwardly visible surface of one or more of the endplates  1102 ,  1105 , and  1114 . In other implementations, the “M” insignia shown in  FIG.  11    is not printed, painted, or adhered on the one or more of the endplates  1102 ,  1105 , and  1114 , and rather is imparted by a mold or machine tool. In still other implementations, the “M” insignia shown in  FIG.  11    has a finish/smoothness that differs from a remainder of the surface of one or more of the endplates  1102 ,  1105 , and  1114 , and the finish of the “M” insignia is achieved by masking off the insignia region while texturizing (e.g., by sandblasting, etching, patterning, painting, etc.) the remainder of the surface of one or more of the endplates  1102 ,  1105 , and  1114 . In some configurations, the “M” insignia has a smooth, mirrored surface and the remainder of the surface of one or more of the endplates  1102 ,  1105 , and  1114  has a matte finish. In other configurations, the “M” insignia has a matte surface and the remainder of the surface of one or more of the endplates  1102 ,  1105 , and  1114  has a smooth, mirrored finish. Although shown and described as an “M,” it should be understood that any letter, numeral, logo, or graphic can be present in place of the “M.” 
     In some embodiments, the numerical indicator  1110  includes or is formed from a plastic resin. The numerical indicator  1110  is optionally textured, and during manufacture/assembly of the smart dumbbell  1100 , the numerical indicator  1110  is inserted into the cutout of the associated endplate, optionally with a precision fit (e.g., a friction fit) such that there is substantially no gap between the numerical indicator  1110  and the cutout, and the outer surface of the relevant endplate is substantially smooth/flush. 
       FIGS.  12 A- 12 D  are diagrams showing an assembled smart dumbbell, in accordance with some embodiments. As shown in  FIG.  12 A , the smart dumbbell  1200  includes a handle  1201  disposed between and connected to each of two weight plate assemblies  1250 A and  1250 B. The weight plate assembly  1250 A includes an endplate  1214  and a numerical indicator  1230 .  FIG.  12 B  shows a battery access door  1252  positioned within an inner endplate  1214 .  FIG.  12 C  shows a view of the smart dumbbell  1200  similar to that of  FIG.  12 B , but with the inner endplate  1214  removed, revealing adhesive tapes  1117 ,  1118 , and  1119 , which secure the inner endplate  1214  to an over-molded weight  1207 .  FIG.  12 D  shows a view of the smart dumbbell  1200  similar to that of  FIG.  12 A , but with the outer endplate  1214  removed, revealing adhesive tapes  1117 ,  1118 , and  1119 , which secure the outer endplate  1214  to the over-molded weight  1207 . 
       FIGS.  13 A- 13 B  are photographs showing a set of smart dumbbells, in accordance with some embodiments. As can be seen in  FIG.  13 A , the handles of the smart dumbbells can increase in thickness and/or length as the weight of the smart dumbbells increases. For example, the thickness and/or length of a 35 lb smart dumbbell can be greater than the thickness and/or length of a 5 lb smart dumbbell. In  FIG.  13 B , a numerical indicator in an illuminated/“on” state is shown at  1330 . 
       FIGS.  14 A- 14 G  are example graphical user interface (GUI) displays showing the generation and display of a universal health score, in accordance with some embodiments. More specifically,  FIG.  14 A  shows an in-workout view of heart rate (see  1402 —graphical depiction of heart rate and numerical heart rate are shown) and heart score  1404 .  FIG.  14 B  shows an in-workout view of repetition counting  1406 .  FIG.  14 C  shows an in-workout view of a muscle exercise with no repetitions (“HOLD”).  FIG.  14 D  shows an in-workout view of a muscle exercise with repetitions (“KEEP MOVING”).  FIG.  14 E  shows an in-workout view of a recovery exercise.  FIG.  14 F  shows a post-workout view of composite exercise scores (heart, muscle, and recovery scores) and a total class score (“78”).  FIG.  14 G  shows a post-workout view of a total class score added to a total health score. As discussed above, and as shown in  FIG.  14 G , a total health score can include three different components—heart (represented by the bar  1408  in  FIG.  14 G ), muscle (represented by the short radial lines  1410  in  FIG.  14 G ), and recovery (represented by the wavy line  1412  in  FIG.  14 G )—and each can represent scores based on a current workout or scores based on a compilation/aggregation of all exercises performed by a given user (e.g., within a predefined time duration, or overall historical).  FIGS.  15 A- 15 H  are additional example GUI displays showing the generation and display of a universal health score, in accordance with some embodiments. 
     As used herein, the terms “substantially,” “approximately,” and “about,” when referencing a numeric value, generally refer to plus or minus 10% of the value stated (e.g., “about 100” would include  90  to  110 ). The term “substantially,” when referencing a non-numeric value, generally means “to a great or significant extent.” For example, “substantially curved” can refer to a shape that approximates a curve but may not be perfectly symmetrical or curvilinear. 
     In some implementations, a smart dumbbell includes a processor and a memory storing processor-executable instructions to “pair” (i.e., wirelessly connect, e.g., via Bluetooth®, Bluetooth Low Energy (BLE), and/or another wireless network communications protocol) the smart dumbbell with a remote compute device, a mobile compute device and/or a smart mirror. The memory can also store processor-executable instructions to perform real-time repetition (“rep”) tracking, form correction, motion tracking, motion monitoring, and/or weight recommendations, any of which may be based on a performance of a user of the smart dumbbell. Optionally, the smart dumbbell also includes one or more sensors, one or more light-emitting diodes (LEDs), and/or a Bluetooth® transceiver. The one or more sensors can include an inertial measurement unit (IMU). For example, a 9-axis IMU may be used, which includes a 3-axis gyroscope, and 3-axis accelerometer, and a 3-axis magnetometer. Using a wireless connection (e.g., Bluetooth® or BLE), the smart dumbbell can transmit position data from the IMU to the remote compute device, mobile compute device and/or smart mirror for further processing. Alternatively or in addition, the one or more sensors can include one or more gyroscopes, one or more accelerometers, one or more magnetometers, one or more pressure sensors, one or more vibration sensors, and/or one or more temperature sensors. Using a wireless connection (e.g., Bluetooth® or BLE), the smart dumbbell can transmit sensor data to the remote compute device, mobile compute device and/or smart mirror for further processing. 
     In some embodiments, a set of smart dumbbells includes one or more of: a 1 lb smart flexible exercise weight, a 1 lb smart dumbbell, a 2 lb smart flexible exercise weight, a 2 lb smart dumbbell, a 3 lb smart dumbbell, a 5 lb smart dumbbell, a 10 lb smart dumbbell, a 15 lb smart dumbbell, a 20 lb smart dumbbell, a 25 lb smart dumbbell, a 30 lb smart dumbbell, a 35 lb smart dumbbell, a 40 lb smart dumbbell, a 45 lb smart dumbbell, or a 50 lb smart dumbbell. The smart dumbbells can include embedded sensors (including one or more of: a gyroscope, an accelerometer, a magnetometer, a pressure sensor, a vibration sensor, and/or a temperature sensor), one or more LEDs, and/or a Bluetooth® transceiver (e.g., for motion tracking and/or monitoring). In some implementations, the smart dumbbells have a fixed weight value (i.e., the weight of the smart dumbbells is not adjustable). In other implementations, the weights of the smart dumbbells can be adjusted. 
     In some implementations, a smart dumbbell includes a processor and a memory storing processor-executable instructions to operate one or more LEDs as an indicator during use of the smart dumbbell. For example, the processor-executable instructions can include instructions to cause the processor to turn on (activate) the one or more LEDs (optionally at a selected predefined wavelength/color of illumination, such as red, green, blue, yellow, orange, violet, white, etc.) in response to detecting that the smart dumbbell is in use (e.g., based on sensor data, such as accelerometer data). Alternatively or in addition, the processor-executable instructions can include instructions to cause the processor to turn on (activate) the one or more LEDs (optionally at a selected predefined wavelength/color of illumination, such as red, green, blue, yellow, orange, violet, white, etc.) in response to one or more of: detecting that a battery charge level of the smart dumbbell is below a predefined threshold, detecting that the smart dumbbell has successfully paired with a smart mirror, or detecting that an attempt to pair the smart dumbbell with a smart mirror has failed or timed out. 
     In some embodiments, after a smart dumbbell has successfully paired with a smart mirror, at least one of the smart dumbbell or the smart mirror can be configured (e.g., via software and/or hardware) to generate a waveform (also referred to herein as a “wave pattern” and used to represent a motion of the smart dumbbell of the user) and/or to count repetitions (“repetition counting”) of a movement of the smart dumbbell, based on data detected at the smart dumbbell (e.g., sensor data, such as IMU position data) and, optionally, based on data received via at least one additional smart dumbbell. The generation of the waveform can be performed using a peak detection algorithm or model, for example according to one or more techniques discussed in “Tracking Free-Weight Exercises” by K. H. Chen, et al., UbiComp 2007: Ubiquitous Computing, Proceedings of the 9 th  International Conference, Innsbruck, Austria, Sep. 16-19, 2007, the entire contents of which are hereby incorporated by reference for all purposes. In some such implementations, the peak detection algorithm or model has been trained to adapt to a detected or specified exercise type associated with the movement of the smart dumbbell. For example, machine learning may be used to train a peak detection model to recognize periods of time in which the smart dumbbell is moving in a first direction, periods of time in which the smart dumbbell is moving in a second direction different from the first direction, and transition or inflection periods during which the smart dumbbell is changing from the first direction to the second direction or from the second direction to the first direction. A repetition can be defined, for example, as a sequential pair of transition or inflection periods, or as a single occurrence of a transition or inflection period. In other such implementations, a plurality of peak detection algorithms may be stored in or accessible to the smart dumbbell and/or the smart mirror, and a peak detection algorithm from the plurality of peak detection algorithms can be automatically selected based on a detected or specified exercise type associated with the movement of the smart dumbbell. By tailoring the algorithm to the specific exercise being performed, a higher precision repetition count can be obtained. 
     Optionally, the at least one of the smart dumbbell or the smart mirror can also be configured (e.g., via software and/or hardware) to detect that the user is moving the smart dumbbell too rapidly or too slowly, e.g., based on the repetition count discussed above. In response to detecting that the user is moving the smart dumbbell too rapidly, the at least one of the smart dumbbell or the smart mirror may generate and display (or cause transmission of) a message recommending that the user switch to a heavier weight and/or recommending that the user modify an aspect of their movement (e.g., “slow down”). Similarly, in response to detecting that the user is moving the smart dumbbell too slowly, the at least one of the smart dumbbell or the smart mirror may generate and display (or cause transmission) of a message recommending that the user switch to a lighter weight and/or recommending that the user modify an aspect of their movement (e.g., “speed up”). 
     Optionally, the at least one of the smart dumbbell or the smart mirror can also be configured (e.g., via software and/or hardware) to detect vibration associated with muscle fatigue or muscle failure. Such vibration may have a predefined “signature,” for example depending on the sensor(s) used, and the signature can include a magnitude, frequency and/or duration of the vibration. In response to detecting no such vibration, the at least one of the smart dumbbell or the smart mirror may generate and display (or cause transmission of) a message recommending that the user switch to a heavier weight and/or recommending that the user modify an aspect of their movement (e.g., “slow down”). In response to detecting such vibration too early within a given exercise period (e.g., “set” of repetitions), the at least one of the smart dumbbell or the smart mirror may generate and display (or cause transmission of) a message recommending that the user switch to a lighter weight and/or recommending that the user modify an aspect of their movement (e.g., “slow down”). In response to detecting such vibration at a preferred time within a given exercise period (e.g., “set” of repetitions), the at least one of the smart dumbbell or the smart mirror may generate and display (or cause transmission of) a message of encouragement to the user and/or cause storage of an indication that the weight is appropriate for that user, for that particular exercise (collectively, “weight data”), so that the weight data can be retrieved at a later time, for example for use in generating and displaying weight recommendations for the same or different exercises. 
     Optionally, the at least one of the smart dumbbell or the smart mirror can also be configured (e.g., via software and/or hardware) to detect an anomalous event or activity (“anomaly”) associated with the user&#39;s movement of the smart dumbbell, e.g., based on the repetition count discussed above. For example, if a detected pattern of movement of the smart dumbbell deviates by more than a predefined amount from a target pattern, the peak detection algorithm or model may generate and/or select a form correction recommendation (or “form tip”) and cause display of a message representing the form tip. An example of a form tip message is “pull your elbows in while doing a bicep curl.” 
     In some implementations, the smart dumbbell can receive data from the smart mirror or other remote compute device (e.g., a mobile compute device such as a smartphone). The at least one LED can be configured to emit patterns, intensities, and/or colors of light to indicate (e.g., using a first color and/or pattern) that data is being received from the smart mirror or other remote compute device and/or to indicate (e.g., using a second color and/or pattern different from the first color and/or pattern) that data is being sent from the apparatus to the smart mirror or other remote compute device. 
     In some implementations, at least one of the smart dumbbell or the smart mirror can detect and/or analyze movements of the user based on data detected, captured, or generated by the smart dumbbell (e.g., accelerometer data) and data detected, captured, or generated by the smart mirror (e.g., video data). The at least one of the smart dumbbell or the smart mirror can generate user appearance data (e.g., in the form of an animation, a reconstruction, a vector representation, a ghosted image, etc., in 2-D or in 3-D) based on the detected and/or analyzed movements of the user, and cause display of the same via the smart mirror, a mobile app, a display of the smart dumbbell and/or a display of a remote compute device. Alternatively, the at least one of the smart dumbbell or the smart mirror can generate such user appearance data without camera/video imagery, and based solely on data detected, captured, or generated by the smart dumbbell. Alternatively, the at least one of the smart dumbbell or the smart mirror can generate such user appearance data based on the data detected, captured, or generated by the smart dumbbell, the data detected, captured, or generated by the smart mirror, and one or more of: smart textiles/garments (i.e., fabric-based sensors), wearable electronics, wearable IMUs, biometric sensors, etc. 
     Additionally, in some implementations, the smart dumbbell can include a rechargeable battery that is at least one of wirelessly rechargeable or rechargeable by cable connection to an external power source. In such implementations, the at least one LED can be configured to emit patterns, intensities, and/or colors of light to indicate a charging status (e.g., currently charging, not charging), a charging progress (e.g., low intensity green light at 10% charged, medium intensity green light at 50% charged, and bright intensity green light at 100% charged). 
     Additionally, in some implementations, the smart dumbbell is a first apparatus that can be configured to connect and communicate with one or more additional apparatuses (which may include other smart dumbbells, smart flexible weights, and/or other smart appliances). For example, in some such implementations, an exercise routine specifies that two smart dumbbells are to be used (e.g., bicep curls). During the exercise routine (e.g., displayed via a smart mirror that is connected wirelessly with at least one of the two smart dumbbells), the at least one LED of one of the smart dumbbells may flash during a time period when that smart dumbbell is to be used (e.g., left bicep curl), and cease flashing when the time period has elapsed. The at least one LED of the other of the smart dumbbells may then begin flashing (corresponding to a second time period during which that smart dumbbell is to be used, e.g., right bicep curl). As another example, even if an exercise routine specifies that only one smart dumbbell is to be used, the at least one LED of one “ideal” smart dumbbell from a set of smart dumbbells may begin flashing to signify to the user that he/she should use that particular weight. The identification of the ideal smart dumbbell can be performed, for example, by the smart mirror (e.g., calculated based on a description of the exercise routine, selected based on a specification input made by an instructor, selected based on a selection input made by the user, calculated/selected based on historical weight data of the user, calculated/selected based on historical preferences of the user, calculated/selected based on historical performance of the user, calculated/selected based on historical scoring of the user, selected based on detected charge levels of one or more smart dumbbells from the set of smart dumbbells, or any of the foregoing in combination). Alternatively, the identification of the ideal smart dumbbell can be performed by a mobile app running on a compute device (e.g., the smartphone of the user, a remote compute device, etc.), where the mobile app is in communication with at least one of the smart mirror or the set of smart dumbbells. 
     In some embodiments, a smart dumbbell has a “stacked” configuration (“stacked smart dumbbell”) where a first plurality of weight plates functions as a first weight plate assembly (e.g., removably installable on a first side of a handle) and a second plurality of weight plates functions as a second weight plate assembly (e.g., removably installable on a second side of the handle). A single weight plate from at least one of the first plurality of weight plates or the second plurality of weight plates can function as an “indicator plate” and include a digital display (e.g., a seven-segment display, a liquid crystal display (LCD), etc.) rather than the numerical indicator described herein. Such stacked smart dumbbells can include a processor operably coupled to a memory storing processor-executable instructions to cause the processor to automatically identify/detect (e.g., in response to detecting a fully-assembled condition) a weight of the stacked smart dumbbell and cause display of the identified/detected weight via the digital display. 
     In some staked smart dumbbell configurations, alternatively or in addition to the foregoing, the processor-executable instructions can include instructions to cause the processor to cause the digital display to output/display a predetermined color, pattern of colors, graphical image, pattern of graphical images, video, or animation. The color, pattern of colors, graphical image, pattern of graphical images, video, or animation can be selected based on a detected status. For example, blue light or an image of water can represent or indicate a low intensity exercise, red light or an image of fire can represent or indicate high intensity exercise, and yellow light or an image of a battery can represent or indicate a low battery condition. The detected status can include at least one of: apparatus in use, apparatus not in use, apparatus at a predefined position, apparatus in motion, battery low, battery charged, successful wireless connection with a remote compute device, failed attempt to wirelessly connect with the remote compute device, repetition number within a set of repetitions, high intensity exercise, low intensity exercise, completion of a set of repetitions, weight too high, weight too low, high score achieved, a predefined time period has elapsed, or a social media event. 
     Universal Health Score (UHS) 
     In some embodiments, at least one of the smart dumbbell or the smart mirror can be configured (e.g., via software and/or hardware) to calculate a Universal Health Score (UHS). The UHS is a holistic way of tracking a user&#39;s progress through a measurement of cardio, strength, and recovery metrics. As an example, during a given fitness class (e.g., a streamed and/or broadcast fitness class displayed via a smart mirror) or exercise period (i.e., a “workout”), a composite score of cardio, strength and/or recovery points for the user can be displayed via the smart mirror or a mobile compute device of the user. The composite score can be based on the types of exercises included within that workout. The user&#39;s “Class Score” at the end of the workout may be added to a “Total Health Score” of the user and saved in a memory of the at least one of the smart dumbbell or the smart mirror, and/or the mobile compute device of the user. 
     Each workout can include a plurality of exercises, and each exercise can be assigned a health type of heart, muscle or recovery. Points associated with each health type can be calculated differently based on a performance of the user. In some implementations, if it is determined (e.g., by the at least one of the smart dumbbell or the smart mirror) that the user does not have a connected peripheral device (e.g., a heart rate monitor, a smart flexible exercise weight, a smart dumbbell, or another biometric sensor), the score(s) may be reduced (e.g., halved). Example calculation details for each exercise type are as follows: 
     Heart 
     In some embodiments, points are earned if a user keep their heart rate in the designated heart rate zone according to the formula: 
         Ph =0.0278*( tz /( tz+abs ( tz−mz ))+0.5 L), 
     where Ph refers to “heart points,” tz is the target heart rate zone for the exercise, mz is the current heart rate zone of the member based on their current heart rate, and L is the exercise level. 
     Muscle 
     In some embodiments, points are earned as a user does repetitions with weights. If the exercise has no repetitions (e.g., during a plank), the user&#39;s score is based on time spent performing the exercise, rather than based on repetitions. When counting repetitions, heavier weights are rewarded with higher point values according to the formula: 
         Pm =(0.0556 /R )*( tw /( tw +( tw−mw ))+0.5 L), 
     where Pm refers to “muscle points,” R is the expected repetition rate per second (with an optional default value of, for example, 2), tw is the target weight for the exercise times the number of weights, mw is the weight in use times the number of weights, and L is the exercise level. If no connected weights (i.e., smart flexible weights and/or smart dumbbells) are active, then the weight value mw is set to be the target weight value (tw), but the points are reduced (e.g., halved) before being applied. 
     Recovery 
     In some embodiments, points are earned for time spent during recovery exercises according to the formula: 
       Pr = 0 . 0278 *  0 . 5 L, 
     where Pr refers to “recovery points” and L is the exercise level. 
     The composite score can be calculated based on each of Ph, Pm, and Pr (e.g., by summing their values, averaging their values, taking a weighted average of their values, etc.). 
     In some embodiments, an apparatus includes a first weight plate, a second weight plate, and an elongate, substantially cylindrical handle. The first weight plate assembly includes a first pair of endplates and a first over-molded weight. The second weight plate assembly includes a second pair of endplates and a second over-molded weight. The handle is mechanically coupled at a first end to the first weight plate assembly and at a second end to the second weight plate assembly. At least one of the first weight plate assembly or the second weight plate assembly includes at least one light-emitting diode (LED) and a transparent or translucent numerical indicator associated with a total weight of the apparatus and through which light emitted from the at least one LED is transmitted when the at least one LED is activated. 
     In some implementations, each of the first over-molded weight and the second over-molded weight includes a metal substrate and a rubber overmolding. 
     In some implementations, the handle has a knurled surface. 
     In some implementations, each of the first over-molded weight and the second over-molded weight has a perimeter surface that defines a double-ridge shape. The perimeter surface can include a texturized rubber surface. 
     In some implementations, the at least one of the first weight plate assembly or the second weight plate assembly includes a battery accessible via a battery door positioned within a surface of the at least one of the first weight endplate assembly or the second weight plate assembly. 
     In some implementations, the numerical indicator is in the shape of a one-digit numeral or a two-digit numeral. 
     In some implementations, the first weight plate assembly includes a first electronics assembly and the second weight plate assembly includes a second electronics assembly, the apparatus further comprising a cable that is electrically connected to each of the first electronics assembly and the second electronics assembly, a portion of the cable being positioned within an interior cavity of the handle. 
     In some implementations, the first weight plate assembly includes a processor operably coupled to a memory storing instructions to cause the processor to perform wireless communications with at least one of: a remote compute device housed within a smart mirror, or a mobile compute device of a user. 
     In some implementations, the first weight plate assembly includes a processor operably coupled to a memory storing instructions to cause the processor to activate the at least one LED in response to at least one of: detecting a connection with a smart mirror, detecting an effort of a user, or detecting a state of a battery of the apparatus. 
     In some embodiments, an apparatus includes a first weight plate assembly, a second weight plate assembly, and an elongate, substantially cylindrical handle. The first weight plate assembly includes a first pair of endplates and a first over-molded weight, and the second weight plate assembly includes a second pair of endplates and a second over-molded weight. The handle is mechanically coupled at a first end to the first weight plate assembly and mechanically coupled at a second end, opposite the first end, to the second weight plate assembly. Each of the first weight plate assembly and the second weight plate assembly has a perimeter surface that defines a double-ridge shape between the pair of endplates for that weight plate assembly. 
     In some implementations, at least one of the first weight plate assembly or the second weight plate assembly includes at least one light-emitting diode (LED) and a transparent or translucent numerical indicator associated with a total weight of the apparatus and through which light emitted from the at least one LED is transmitted when the at least one LED is activated. 
     In some implementations, the at least one of the first weight plate assembly or the second weight plate assembly includes a battery accessible via a battery door positioned within a surface of the associated pair of endplates. 
     In some implementations, the perimeter surface is a texturized rubber surface. 
     In some implementations, the first weight plate assembly includes a first electronics assembly and the second weight plate assembly includes a second electronics assembly, the apparatus further comprising a cable that is electrically connected to each of the first electronics assembly and the second electronics assembly, a portion of the cable being positioned within an interior cavity of the handle. 
     In some implementations, the first weight plate assembly includes a processor operably coupled to a memory storing instructions to cause the processor to perform wireless communications with at least one of: a remote compute device housed within a smart mirror, or a mobile compute device of the user. 
     In some embodiments, an apparatus includes a first weight plate assembly, a second weight plate assembly, and an elongate, substantially cylindrical handle. The first weight plate assembly includes a first pair of endplates and a first over-molded weight. The second weight plate assembly includes a second pair of endplates and a second over-molded weight. The handle is mechanically coupled at a first end to the first weight plate assembly and is mechanically coupled at a second end, opposite the first end, to the second weight plate assembly. At least one of the first weight plate assembly or the second weight plate assembly includes at least one light-emitting diode (LED). At least one of the first weight plate assembly or the second weight plate assembly including a processor operably coupled to a memory storing instructions to cause the processor to activate the at least one LED in response to detecting a status associated with at least one of the apparatus, a user of the apparatus, or a workout being performed by the user of the apparatus. 
     In some implementations, the instructions to cause the processor to activate the at least one LED include instructions to activate the at least one LED such that the LED emits light having a predetermined color, the predetermined color being selected based on the detected status. For example, blue light can represent or indicate a low intensity exercise, red light can represent or indicate high intensity exercise, and yellow light can represent or indicate a low battery condition. 
     In some implementations, the instructions to cause the processor to activate the at least one LED include instructions to activate the at least one LED such that the LED emits light in a predetermined pattern, the predetermined pattern being selected based on the detected status. For example, a blinking light (optionally in combination with a color of light, such as yellow) can represent a low battery condition. As another example, a steady/continuous light can represent or indicate that the smart dumbbell is connected to a smart mirror or other remote compute device. 
     In some implementations, the status includes at least one of: apparatus in use, apparatus not in use, apparatus at a predefined position, apparatus in motion, battery low, battery charged, successful wireless connection with a remote compute device, failed attempt to wirelessly connect with the remote compute device, repetition number within a set of repetitions, high intensity exercise, low intensity exercise, completion of a set of repetitions, weight too high, weight too low, high score achieved, a predefined time period has elapsed, or a social media event. 
     All combinations of the foregoing concepts and additional concepts discussed herewithin (provided such concepts are not mutually inconsistent) are contemplated as being part of the subject matter disclosed herein. The terminology explicitly employed herein that also may appear in any disclosure incorporated by reference should be accorded a meaning most consistent with the particular concepts disclosed herein. 
     The drawings are primarily for illustrative purposes, and are not intended to limit the scope of the subject matter described herein. The drawings are not necessarily to scale; in some instances, various aspects of the subject matter disclosed herein may be shown exaggerated or enlarged in the drawings to facilitate an understanding of different features. In the drawings, like reference characters generally refer to like features (e.g., functionally similar and/or structurally similar elements). 
     The entirety of this application (including the Cover Page, Title, Headings, Background, Summary, Brief Description of the Drawings, Detailed Description, Embodiments, Abstract, Figures, Appendices, and otherwise) shows, by way of illustration, various embodiments in which the embodiments may be practiced. The advantages and features of the application are of a representative sample of embodiments only, and are not exhaustive and/or exclusive. Rather, they are presented to assist in understanding and teach the embodiments, and are not representative of all embodiments. As such, certain aspects of the disclosure have not been discussed herein. That alternate embodiments may not have been presented for a specific portion of the innovations or that further undescribed alternate embodiments may be available for a portion is not to be considered to exclude such alternate embodiments from the scope of the disclosure. It will be appreciated that many of those undescribed embodiments incorporate the same principles of the innovations and others are equivalent. Thus, it is to be understood that other embodiments may be utilized and functional, logical, operational, organizational, structural and/or topological modifications may be made without departing from the scope and/or spirit of the disclosure. As such, all examples and/or embodiments are deemed to be non-limiting throughout this disclosure. 
     Also, no inference should be drawn regarding those embodiments discussed herein relative to those not discussed herein other than it is as such for purposes of reducing space and repetition. For instance, it is to be understood that the logical and/or topological structure of any combination of any program components (a component collection), other components and/or any present feature sets as described in the figures and/or throughout are not limited to a fixed operating order and/or arrangement, but rather, any disclosed order is exemplary and all equivalents, regardless of order, are contemplated by the disclosure. 
     Various concepts may be embodied as one or more methods, of which at least one example has been provided. The acts performed as part of the method may be ordered in any suitable way. Accordingly, embodiments may be constructed in which acts are performed in an order different than illustrated, which may include performing some acts simultaneously, even though shown as sequential acts in illustrative embodiments. Put differently, it is to be understood that such features may not necessarily be limited to a particular order of execution, but rather, any number of threads, processes, services, servers, and/or the like that may execute serially, asynchronously, concurrently, in parallel, simultaneously, synchronously, and/or the like in a manner consistent with the disclosure. As such, some of these features may be mutually contradictory, in that they cannot be simultaneously present in a single embodiment. Similarly, some features are applicable to one aspect of the innovations, and inapplicable to others. 
     The term “automatically” is used herein to modify actions that occur without direct input or prompting by an external source such as a user. Automatically occurring actions can occur periodically, sporadically, in response to a detected event (e.g., a user logging in), or according to a predetermined schedule. 
     The term “determining” encompasses a wide variety of actions and, therefore, “determining” can include calculating, computing, processing, deriving, investigating, looking up (e.g., looking up in a table, a database or another data structure), ascertaining and the like. Also, “determining” can include receiving (e.g., receiving information), accessing (e.g., accessing data in a memory) and the like. Also, “determining” can include resolving, selecting, choosing, establishing and the like. 
     The phrase “based on” does not mean “based only on,” unless expressly specified otherwise. In other words, the phrase “based on” describes both “based only on” and “based at least on.” 
     Some embodiments and/or methods described herein can be performed by software (executed on hardware), hardware, or a combination thereof. Hardware modules may include, for example, a processor, a field programmable gate array (FPGA), and/or an application specific integrated circuit (ASIC). Software modules (executed on hardware) can include instructions stored in a memory that is operably coupled to a processor, and can be expressed in a variety of software languages (e.g., computer code), including C, C++, Java™, Ruby, Visual Basic™, and/or other object-oriented, procedural, or other programming language and development tools. Examples of computer code include, but are not limited to, micro-code or micro-instructions, machine instructions, such as produced by a compiler, code used to produce a web service, and files containing higher-level instructions that are executed by a computer using an interpreter. For example, embodiments may be implemented using imperative programming languages (e.g., C, Fortran, etc.), functional programming languages (Haskell, Erlang, etc.), logical programming languages (e.g., Prolog), object-oriented programming languages (e.g., Java, C++, etc.) or other suitable programming languages and/or development tools. Additional examples of computer code include, but are not limited to, control signals, encrypted code, and compressed code. 
     The term “processor” should be interpreted broadly to encompass a general purpose processor, a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a controller, a microcontroller, a state machine and so forth. Under some circumstances, a “processor” may refer to an application specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), etc. The term “processor” may refer to a combination of processing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core or any other such configuration. 
     The term “memory” should be interpreted broadly to encompass any electronic component capable of storing electronic information. The term memory may refer to various types of processor-readable media such as random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erasable programmable read only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, magnetic or optical data storage, registers, etc. Memory is said to be in electronic communication with a processor if the processor can read information from and/or write information to the memory. Memory that is integral to a processor is in electronic communication with the processor. 
     The terms “instructions” and “code” should be interpreted broadly to include any type of computer-readable statement(s). For example, the terms “instructions” and “code” may refer to one or more programs, routines, sub-routines, functions, procedures, etc. “Instructions” and “code” may comprise a single computer-readable statement or many computer-readable statements. 
     Some embodiments described herein relate to a computer storage product with a non-transitory computer-readable medium (also can be referred to as a non-transitory processor-readable medium) having instructions or computer code thereon for performing various computer-implemented operations. The computer-readable medium (or processor-readable medium) is non-transitory in the sense that it does not include transitory propagating signals per se (e.g., a propagating electromagnetic wave carrying information on a transmission medium such as space or a cable). The media and computer code (also can be referred to as code) may be those designed and constructed for the specific purpose or purposes. Examples of non-transitory computer-readable media include, but are not limited to, magnetic storage media such as hard disks, floppy disks, and magnetic tape; optical storage media such as Compact Disc/Digital Video Discs (CD/DVDs), Compact Disc-Read Only Memories (CD-ROMs), and holographic devices; magneto-optical storage media such as optical disks; carrier wave signal processing modules; and hardware devices that are specially configured to store and execute program code, such as Application-Specific Integrated Circuits (ASICs), Programmable Logic Devices (PLDs), Read-Only Memory (ROM) and Random-Access Memory (RAM) devices. Other embodiments described herein relate to a computer program product, which can include, for example, the instructions and/or computer code discussed herein. 
     Some embodiments and/or methods described herein can be performed by software (executed on hardware), hardware, or a combination thereof. Hardware modules may include, for example, a general-purpose processor, a field programmable gate array (FPGA), and/or an application specific integrated circuit (ASIC). Software modules (executed on hardware) can be expressed in a variety of software languages (e.g., computer code), including C, C++, Java™, Ruby, Visual Basic™, and/or other object-oriented, procedural, or other programming language and development tools. Examples of computer code include, but are not limited to, micro-code or micro-instructions, machine instructions, such as produced by a compiler, code used to produce a web service, and files containing higher-level instructions that are executed by a computer using an interpreter. For example, embodiments may be implemented using imperative programming languages (e.g., C, Fortran, etc.), functional programming languages (Haskell, Erlang, etc.), logical programming languages (e.g., Prolog), object-oriented programming languages (e.g., Java, C++, etc.) or other suitable programming languages and/or development tools. Additional examples of computer code include, but are not limited to, control signals, encrypted code, and compressed code. 
     Various concepts may be embodied as one or more methods, of which at least one example has been provided. The acts performed as part of the method may be ordered in any suitable way. Accordingly, embodiments may be constructed in which acts are performed in an order different than illustrated, which may include performing some acts simultaneously, even though shown as sequential acts in illustrative embodiments. Put differently, it is to be understood that such features may not necessarily be limited to a particular order of execution, but rather, any number of threads, processes, services, servers, and/or the like that may execute serially, asynchronously, concurrently, in parallel, simultaneously, synchronously, and/or the like in a manner consistent with the disclosure. As such, some of these features may be mutually contradictory, in that they cannot be simultaneously present in a single embodiment. Similarly, some features are applicable to one aspect of the innovations, and inapplicable to others. 
     In addition, the disclosure may include other innovations not presently described. Applicant reserves all rights in such innovations, including the right to embodiment such innovations, file additional applications, continuations, continuations-in-part, divisionals, and/or the like thereof. As such, it should be understood that advantages, embodiments, examples, functional, features, logical, operational, organizational, structural, topological, and/or other aspects of the disclosure are not to be considered limitations on the disclosure as defined by the embodiments or limitations on equivalents to the embodiments. Depending on the particular desires and/or characteristics of an individual and/or enterprise user, database configuration and/or relational model, data type, data transmission and/or network framework, syntax structure, and/or the like, various embodiments of the technology disclosed herein may be implemented in a manner that enables a great deal of flexibility and customization as described herein. 
     All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms. 
     As used herein, in particular embodiments, the terms “about” or “approximately” when preceding a numerical value indicates the value plus or minus a range of 10%. Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range is encompassed within the disclosure. That the upper and lower limits of these smaller ranges can independently be included in the smaller ranges is also encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure. 
     The indefinite articles “a” and “an,” as used herein in the specification and in the embodiments, unless clearly indicated to the contrary, should be understood to mean “at least one.” 
     The phrase “and/or,” as used herein in the specification and in the embodiments, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc. 
     As used herein in the specification and in the embodiments, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of” or “exactly one of,” or, when used in the embodiments, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.” “Consisting essentially of,” when used in the embodiments, shall have its ordinary meaning as used in the field of patent law. 
     As used herein in the specification and in the embodiments, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc. 
     In the embodiments, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03.