Patent Publication Number: US-2023148905-A1

Title: Fitness Training System for Merging Energy Expenditure Calculations from Multiple Devices

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present application is a continuation of U.S. patent application Ser. No. 17/352,932, filed Jun. 21, 2021, which is a continuation of U.S. patent application Ser. No. 16/199,874, filed Nov. 26, 2018, now U.S. Pat. No. 11,045,114 issued Jun. 29, 2021, which is a continuation of U.S. patent application Ser. No. 14/513,540, filed on Oct. 14, 2014, now U.S. Pat. No. 10,136,840 issued Nov. 27, 2018, which claims benefit to U.S. Provisional Application No. 61/890,672, filed Oct. 14, 2013, all of which are incorporated by reference herein in their entirety for any and all non-limiting purposes. 
    
    
     BACKGROUND 
     While most people appreciate the importance of physical fitness, many have difficulty finding the motivation required to maintain a regular exercise program. Some people find it particularly difficult to maintain an exercise regimen that involves continuously repetitive motions, such as running, walking and bicycling. 
     Additionally, individuals may view exercise as work or a chore and thus, separate it from enjoyable aspects of their daily lives. Often, this clear separation between athletic activity and other activities reduces the amount of motivation that an individual might have toward exercising. Further, athletic activity services and systems directed toward encouraging individuals to engage in athletic activities might also be too focused on one or more particular activities while an individual&#39;s interest are ignored. This may further decrease a user&#39;s interest in participating in athletic activities or using the athletic activity services and systems. 
     Therefore, improved systems and methods to address these and other shortcomings in the art are desired. 
     BRIEF SUMMARY 
     The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosure. The summary is not an extensive overview of the disclosure. It is neither intended to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure. The following summary merely presents some concepts of the disclosure in a simplified form as a prelude to the description below. 
     Aspects of this disclosure relate to processing of data taken while a user performs an athletic activity to determine an estimate of energy expenditure such as, for example, an amount of calories burned. 
     An illustrative apparatus for use with a user performing an exercise may include at least one processor, a first sensor, a communication circuit and at least one tangible memory. In some cases, the first sensor may be configured to monitor a first exercise performed by the user. The communication circuit may be configured to communicate at least energy expenditure information between the apparatus and at least a second device, the energy expenditure information including at least a first energy expenditure estimate corresponding to the first exercise monitored by the first sensor and a second energy expenditure estimate corresponding to a second exercise monitored by at least the second device. In some cases, the at least one tangible memory may be store computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to monitor, with the sensor, the first exercise performed by the user and/or determine, by the at least one processor, the first energy expenditure estimate of the user corresponding to the monitored first exercise. In some cases, the computer-executable instructions, when executed by the processor, may cause the illustrative apparatus to communicate, by the communication circuit, energy expenditure information between the apparatus and at least the second device. The energy expenditure information may include the first energy expenditure estimate and the second energy expenditure estimate. The computer-executable instructions, when executed by the processor, may further cause the illustrative apparatus to determine, by the at least one processor, a combined energy expenditure estimate of the user based, at least in part, on the first energy expenditure estimate and the second energy expenditure estimate. 
     In some cases, an illustrative system may include at least a first monitoring device configured to determine a first energy expenditure estimate associated with athletic activity performed by a user over a first duration and a second device, in communication with the first monitoring device, the second device configured to store at least a second energy expenditure estimate associated with athletic activity performed by the same user over a second duration. The first monitoring device may include a first processor and a first tangible memory device. In some cases, the first tangible memory device may store computer-executable instructions that, when executed by the first processor, may cause the first monitoring device at least to send, the first energy expenditure estimate to the second device, receive the second energy expenditure estimate from the second device, and determine, by the processor, a total energy expenditure estimate based, at least in part, on the first energy expenditure estimate and the second energy expenditure estimate. In some cases, the illustrative system may include a display to display the total energy expenditure estimate to the user. 
     Illustrative embodiments may relate to a system, method, apparatus, and computer readable media configured for determining first energy expenditure information associated with a first athletic activity of the user, synchronizing the first energy expenditure information with second energy expenditure information of a second device, determining a total energy expenditure estimate based, at least in part, on the first energy expenditure information and the second energy expenditure information, and displaying the total energy expenditure estimate, such as to a user. In some cases, the first energy expenditure information and/or the second energy expenditure information may include a first energy expenditure estimate and a first time stamp associated with the first athletic activity, 
     These and other aspects of the embodiments are discussed in greater detail throughout this disclosure, including the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present disclosure is illustrated by way of example and not limited in the accompanying figures in which like reference numerals indicate similar elements and in which: 
         FIGS.  1 A-B  illustrate an example of a system for providing personal training in accordance with example embodiments, wherein  FIG.  1 A  illustrates an example network configured to monitor athletic activity, and  FIG.  1 B  illustrates an example computing device in accordance with example embodiments. 
         FIGS.  2 A-B  illustrate example sensor assemblies that may be worn by a user in accordance with example embodiments. 
         FIG.  3    illustrates an example flow diagram of a method for calculating an energy expenditure estimate for a user that accounts for a user&#39;s form while exercising as part of the estimate, in accordance with example embodiments. 
         FIG.  4    illustrates example points on a user&#39;s body for monitoring during exercising in accordance with example embodiments. 
         FIG.  5    illustrates an example posture assessment in accordance with example embodiments. 
         FIG.  6    illustrates example displays of a virtual avatar of a user performing an exercise in accordance with example embodiments. 
         FIGS.  7 A-B  illustrate example displays of a virtual avatar of a user performing a squat in accordance with example embodiments. 
         FIG.  8    illustrates an example flow diagram of a method for calculating an energy expenditure estimate for a user while performing an athletic activity based on monitoring changes in potential energy, in accordance with example embodiments. 
         FIGS.  9 ,  10 A -B, and  11  illustrate example locations of centers of mass for a virtual avatar of user, in accordance with example embodiments. 
         FIG.  12    illustrates an example of a system for determining a total energy expenditure of a user over a specified duration. 
         FIGS.  13 A-B  show illustrative charts showing use of two or more devices capable of monitoring energy expenditure of a user while performing one or more athletic activities and/or exercises. 
         FIGS.  14 A-B  show illustrative block diagram representations of at least a portion of a device  1400 ,  1450  for determining and/or displaying energy expenditure estimates. 
         FIG.  15    illustrates an example flow diagram of a method for calculating a combined energy expenditure estimate for a user based on energy expenditure estimates obtained by two or more different devices. 
         FIG.  16    shows an illustrative chart showing use of two devices capable of monitoring energy expenditure of a user while performing one or more athletic activities and/or exercises over a common time interval. 
         FIG.  17    shows an illustrative charts showing use of two devices capable of monitoring energy expenditure of a user while performing one or more athletic activities and/or exercises over a common time interval. 
     
    
    
     DETAILED DESCRIPTION 
     In the following description of the various embodiments, reference is made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration various embodiments in which the disclosure may be practiced. It is to be understood that other embodiments may be utilized and structural and functional modifications may be made without departing from the scope and spirit of the present disclosure. Further, headings within this disclosure should not be considered as limiting aspects of the disclosure. Those skilled in the art with the benefit of this disclosure will appreciate that the example embodiments are not limited to the example headings. 
     I. Example Personal Training System 
     A. Illustrative Computing Devices 
       FIG.  1 A  illustrates an example of a personal training system  100  in accordance with example embodiments. Example system  100  may include one or more electronic devices, such as computer  102 . Computer  102  may comprise a mobile terminal, such as a telephone, music player, tablet, netbook or any portable device. In other embodiments, computer  102  may comprise a set-top box (STB), desktop computer, digital video recorder(s) (DVR), computer server(s), and/or any other desired computing device. In certain configurations, computer  102  may comprise a gaming console, such as for example, a Microsoft® XBOX, Sony® Playstation, and/or a Nintendo® Wii gaming consoles. Those skilled in the art will appreciate that these are merely example consoles for descriptive purposes and this disclosure is not limited to any console or device. 
     Turning briefly to  FIG.  1 B , computer  102  may include computing unit  104 , which may comprise at least one processing unit  106 . Processing unit  106  may be any type of processing device for executing software instructions, such as for example, a microprocessor device. Computer  102  may include a variety of non-transitory computer readable media, such as memory  108 . Memory  108  may include, but is not limited to, random access memory (RAM) such as RAM  110 , and/or read only memory (ROM), such as ROM  112 . Memory  108  may include any of: electronically erasable programmable read only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by computer  102 . 
     The processing unit  106  and the system memory  108  may be connected, either directly or indirectly, through a bus  114  or alternate communication structure to one or more peripheral devices. For example, the processing unit  106  or the system memory  108  may be directly or indirectly connected to additional memory storage, such as a hard disk drive  116 , a removable magnetic disk drive, an optical disk drive  118 , and a flash memory card. The processing unit  106  and the system memory  108  also may be directly or indirectly connected to one or more input devices  120  and one or more output devices  122 . The output devices  122  may include, for example, a display device  136 , television, printer, stereo, or speakers. In some embodiments one or more display devices may be incorporated into eyewear. The display devices incorporated into eyewear may provide feedback to users. Eyewear incorporating one or more display devices also provides for a portable display system. The input devices  120  may include, for example, a keyboard, touch screen, a remote control pad, a pointing device (such as a mouse, touchpad, stylus, trackball, or joystick), a scanner, a camera or a microphone. In this regard, input devices  120  may comprise one or more sensors configured to sense, detect, and/or measure athletic movement from a user, such as user  124 , shown in  FIG.  1 A . 
     Looking again to  FIG.  1 A , image-capturing device  126  and/or sensor  128  may be utilized in detecting and/or measuring athletic movements of user  124 . In one embodiment, data obtained from image-capturing device  126  or sensor  128  may directly detect athletic movements, such that the data obtained from image-capturing device  126  or sensor  128  is directly correlated to a motion parameter. For example, and with reference to  FIG.  4   , image data from image-capturing device  126  may detect that the distance between sensor locations  402   g  and  402   i  has decreased and therefore, image-capturing device  126  alone may be configured to detect that user&#39;s  124  right arm has moved. Yet, in other embodiments, data from image-capturing device  126  and/or sensor  128  may be utilized in combination, either with each other or with other sensors to detect and/or measure movements. Thus, certain measurements may be determined from combining data obtained from two or more devices. Image-capturing device  126  and/or sensor  128  may include or be operatively connected to one or more sensors, including but not limited to: an accelerometer, a gyroscope, a location-determining device (e.g., GPS), light sensor, temperature sensor (including ambient temperature and/or body temperature), heart rate monitor, image-capturing sensor, moisture sensor and/or combinations thereof. Example uses of illustrative sensors  126 ,  128  are provided below in Section I.C, entitled “Illustrative Sensors.” Computer  102  may also use touch screens or image capturing device to determine where a user is pointing to make selections from a graphical user interface. One or more embodiments may utilize one or more wired and/or wireless technologies, alone or in combination, wherein examples of wireless technologies include Bluetooth® technologies, Bluetooth® low energy technologies, and/or ANT technologies. 
     B. Illustrative Network 
     Still further, computer  102 , computing unit  104 , and/or any other electronic devices may be directly or indirectly connected to one or more network interfaces, such as example interface  130  (shown in  FIG.  1 B ) for communicating with a network, such as network  132 . In the example of  FIG.  1 B , network interface  130 , may comprise a network adapter or network interface card (NIC) configured to translate data and control signals from the computing unit  104  into network messages according to one or more communication protocols, such as the Transmission Control Protocol (TCP), the Internet Protocol (IP), and the User Datagram Protocol (UDP). These protocols are well known in the art, and thus will not be discussed here in more detail. An interface  130  may employ any suitable connection agent for connecting to a network, including, for example, a wireless transceiver, a power line adapter, a modem, or an Ethernet connection. Network  132 , however, may be any one or more information distribution network(s), of any type(s) or topology(s), alone or in combination(s), such as internet(s), intranet(s), cloud(s), LAN(s). Network  132  may be any one or more of cable, fiber, satellite, telephone, cellular, wireless, etc. Networks are well known in the art, and thus will not be discussed here in more detail. Network  132  may be variously configured such as having one or more wired or wireless communication channels to connect one or more locations (e.g., schools, businesses, homes, consumer dwellings, network resources, etc.), to one or more remote servers  134 , or to other computers, such as similar or identical to computer  102 . Indeed, system  100  may include more than one instance of each component (e.g., more than one computer  102 , more than one display  136 , etc.). 
     Regardless of whether computer  102  or other electronic device within network  132  is portable or at a fixed location, it should be appreciated that, in addition to the input, output and storage peripheral devices specifically listed above, the computing device may be connected, such as either directly, or through network  132  to a variety of other peripheral devices, including some that may perform input, output and storage functions, or some combination thereof In certain embodiments, a single device may integrate one or more components shown in  FIG.  1 A . For example, a single device may include computer  102 , image-capturing device  126 , sensor  128 , display  136  and/or additional components. In one embodiment, sensor device  138  may comprise a mobile terminal having a display  136 , image-capturing device  126 , and one or more sensors  128 . Yet, in another embodiment, image-capturing device  126 , and/or sensor  128  may be peripherals configured to be operatively connected to a media device, including for example, a gaming or media system. Thus, it goes from the foregoing that this disclosure is not limited to stationary systems and methods. Rather, certain embodiments may be carried out by a user  124  in almost any location. 
     C. Illustrative Sensors 
     Computer  102  and/or other devices may comprise one or more sensors  126 ,  128  configured to detect and/or monitor at least one fitness parameter of a user  124 . Sensors  126  and/or  128  may include, but are not limited to: an accelerometer, a gyroscope, a location-determining device (e.g., GPS), light sensor, temperature sensor (including ambient temperature and/or body temperature), sleep pattern sensors, heart rate monitor, image-capturing sensor, moisture sensor and/or combinations thereof. Network  132  and/or computer  102  may be in communication with one or more electronic devices of system  100 , including for example, display  136 , an image capturing device  126  (e.g., one or more video cameras), and sensor  128 , which may be an infrared (IR) device. In one embodiment sensor  128  may comprise an IR transceiver. For example, sensors  126 , and/or  128  may transmit waveforms into the environment, including towards the direction of user  124  and receive a “reflection” or otherwise detect alterations of those released waveforms. In yet another embodiment, image-capturing device  126  and/or sensor  128  may be configured to transmit and/or receive other wireless signals, such as radar, sonar, and/or audible information. Those skilled in the art will readily appreciate that signals corresponding to a multitude of different data spectrums may be utilized in accordance with various embodiments. In this regard, sensors  126  and/or  128  may detect waveforms emitted from external sources (e.g., not system  100 ). For example, sensors  126  and/or  128  may detect heat being emitted from user  124  and/or the surrounding environment. Thus, image-capturing device  126  and/or sensor  128  may comprise one or more thermal imaging devices. In one embodiment, image-capturing device  126  and/or sensor  128  may comprise an IR device configured to perform range phenomenology. As a non-limited example, image-capturing devices configured to perform range phenomenology are commercially available from Flir Systems, Inc. of Portland, Oreg. Although image capturing device  126  and sensor  128  and display  136  are shown in direct (wirelessly or wired) communication with computer  102 , those skilled in the art will appreciate that any may directly communicate (wirelessly or wired) with network  132 . 
     1. Multi-Purpose Electronic Devices 
     User  124  may possess, carry, and/or wear any number of electronic devices, including sensory devices  138 ,  140 ,  142 , and/or  144 . In certain embodiments, one or more devices  138 ,  140 ,  142 ,  144  may not be specially manufactured for fitness or athletic purposes. Indeed, aspects of this disclosure relate to utilizing data from a plurality of devices, some of which are not fitness devices, to collect, detect, and/or measure athletic data. In one embodiment, device  138  may comprise a portable electronic device, such as a telephone or digital music player, including an IPOD®, IPAD®, or iPhone®, brand devices available from Apple, Inc. of Cupertino, Calif., devices operating using the Android® platform available from Google, Inc. of Mountain View, Calif., or Zune® or Microsoft® Windows devices available from Microsoft of Redmond, Wash., or the like. As known in the art, digital media players can serve as both an output device for a computer (e.g., outputting music from a sound file or pictures from an image file) and a storage device. In one embodiment, device  138  may be computer  102 , yet in other embodiments, computer  102  may be entirely distinct from device  138 . Regardless of whether device  138  is configured to provide certain output, it may serve as an input device for receiving sensory information. Devices  138 ,  140 ,  142 , and/or  144  may include one or more sensors, including but not limited to: an accelerometer, a gyroscope, a location-determining device (e.g., GPS), light sensor, temperature sensor (including ambient temperature and/or body temperature), heart rate monitor, image-capturing sensor, moisture sensor and/or combinations thereof In certain embodiments, sensors may be passive, such as reflective materials that may be detected by image-capturing device  126  and/or sensor  128  (among others). In certain embodiments, sensors  144  may be integrated into apparel, such as athletic clothing. For instance, the user  124  may wear one or more on-body sensors  144   a - b . Sensors  144  may be incorporated into the clothing of user  124  and/or placed at any desired location of the body of user  124 . Sensors  144  may communicate (e.g., wirelessly) with computer  102 , sensors  128 ,  138 ,  140 , and  142 , and/or camera  126 . Examples of interactive gaming apparel are described in U.S. Pat. App. No. 10/286,396, filed Oct. 30, 2002, and published as U.S. Pat. Pub, No. 2004/0087366, the contents of which are incorporated herein by reference in its entirety for any and all non-limiting purposes. In certain embodiments, passive sensing surfaces may reflect waveforms, such as infrared light, emitted by image-capturing device  126  and/or sensor  128 . In one embodiment, passive sensors located on user&#39;s  124  apparel may comprise generally spherical structures made of glass or other transparent or translucent surfaces which may reflect waveforms. Different classes of apparel may be utilized in which a given class of apparel has specific sensors configured to be located proximate to a specific portion of the user&#39;s  124  body when properly worn. For example, golf apparel may include one or more sensors positioned on the apparel in a first configuration and yet soccer apparel may include one or more sensors positioned on apparel in a second configuration. 
     Devices  138 - 144  may communicate with each other, either directly or through a network, such as network  132 . Communication between one or more of devices  138 - 144  may communicate through computer  102 . For example, two or more of devices  138 - 144  may be peripherals operatively connected to bus  114  of computer  102 . In yet another embodiment, a first device, such as device  138  may communicate with a first computer, such as computer  102  as well as another device, such as device  142 , however, device  142  may not be configured to connect to computer  102  but may communicate with device  138 . Those skilled in the art will appreciate that other configurations are possible. 
     Some implementations of the example embodiments may alternately or additionally employ computing devices that are intended to be capable of a wide variety of functions, such as a desktop or laptop personal computer. These computing devices may have any combination of peripheral devices or additional components as desired. Also, the components shown in  FIG.  1 B  may be included in the server  134 , other computers, apparatuses, etc. 
     2. Illustrative Apparel/Accessory Sensors 
     In certain embodiments, sensory devices  138 ,  140 ,  142  and/or  144  may be formed within or otherwise associated with user&#39;s  124  clothing or accessories, including a watch, armband, wristband, necklace, shirt, shoe, or the like. Examples of shoe-mounted and wrist-worn devices (devices  140  and  142 , respectively) are described immediately below, however, these are merely example embodiments and this disclosure should not be limited to such. 
     i. Shoe-Mounted Device 
     In certain embodiments, sensory device  140  may comprise footwear which may include one or more sensors, including but not limited to: an accelerometer, location-sensing components, such as GPS, and/or a force sensor system.  FIG.  2 A  illustrates one example embodiment of a sensor system  202 . In certain embodiments, system  202  may include a sensor assembly  204 . Assembly  204  may comprise one or more sensors, such as for example, an accelerometer, location-determining components, and/or force sensors. In the illustrated embodiment, assembly  204  incorporates a plurality of sensors, which may include force-sensitive resistor (FSR) sensors  206 . In yet other embodiments, other sensor(s) may be utilized. Port  208  may be positioned within a sole structure  209  of a shoe. Port  208  may optionally be provided to be in communication with an electronic module  210  (which may be in a housing  211 ) and a plurality of leads  212  connecting the FSR sensors  206  to the port  208 . Module  210  may be contained within a well or cavity in a sole structure of a shoe. The port  208  and the module  210  include complementary interfaces  214 ,  216  for connection and communication. 
     In certain embodiments, at least one force-sensitive resistor  206  shown in  FIG.  2 A  may contain first and second electrodes or electrical contacts  218 ,  220  and a force-sensitive resistive material  222  disposed between the electrodes  218 ,  220  to electrically connect the electrodes  218 ,  220  together. When pressure is applied to the force-sensitive material  222 , the resistivity and/or conductivity of the force-sensitive material  222  changes, which changes the electrical potential between the electrodes  218 ,  220 . The change in resistance can be detected by the sensor system  202  to detect the force applied on the sensor  216 . The force-sensitive resistive material  222  may change its resistance under pressure in a variety of ways. For example, the force-sensitive material  222  may have an internal resistance that decreases when the material is compressed, similar to the quantum tunneling composites described in greater detail below. Further compression of this material may further decrease the resistance, allowing quantitative measurements, as well as binary (on/off) measurements. In some circumstances, this type of force-sensitive resistive behavior may be described as “volume-based resistance,” and materials exhibiting this behavior may be referred to as “smart materials.” As another example, the material  222  may change the resistance by changing the degree of surface-to-surface contact. This can be achieved in several ways, such as by using microprojections on the surface that raise the surface resistance in an uncompressed condition, where the surface resistance decreases when the microprojections are compressed, or by using a flexible electrode that can be deformed to create increased surface-to-surface contact with another electrode. This surface resistance may be the resistance between the material  222  and the electrode  218 ,  220   222  and/or the surface resistance between a conducting layer (e.g., carbon/graphite) and a force-sensitive layer (e.g., a semiconductor) of a multi-layer material  222 . The greater the compression, the greater the surface-to-surface contact, resulting in lower resistance and enabling quantitative measurement. In some circumstances, this type of force-sensitive resistive behavior may be described as “contact-based resistance.” It is understood that the force-sensitive resistive material  222 , as defined herein, may be or include a doped or non-doped semiconducting material. 
     The electrodes  218 ,  220  of the FSR sensor  216  can be formed of any conductive material, including metals, carbon/graphite fibers or composites, other conductive composites, conductive polymers or polymers containing a conductive material, conductive ceramics, doped semiconductors, or any other conductive material. The leads  212  can be connected to the electrodes  218 ,  220  by any suitable method, including welding, soldering, brazing, adhesively joining, fasteners, or any other integral or non-integral joining method. Alternately, the electrode  218 ,  220  and associated lead  212  may be formed of a single piece of the same material. 
     ii. Wrist-Worn Device 
     As shown in  FIG.  2 B , device  226  (which may resemble or be sensory device  142  shown in  FIG.  1 A ) may be configured to be worn by user  124 , such as around a wrist, arm, ankle or the like. Device  226  may monitor athletic movements of a user, including all-day activity of user  124 . In this regard, device assembly  226  may detect athletic movement during user&#39;s  124  interactions with computer  102  and/or operate independently of computer  102 . For example, in one embodiment, device  226  may be an-all day activity monitor that measures activity regardless of the user&#39;s proximity or interactions with computer  102 . Device  226  may communicate directly with network  132  and/or other devices, such as devices  138  and/or  140 . In other embodiments, athletic data obtained from device  226  may be utilized in determinations conducted by computer  102 , such as determinations relating to which exercise programs are presented to user  124 . In one embodiment, device  226  may also wirelessly interact with a mobile device, such as device  138  associated with user  124  or a remote website such as a site dedicated to fitness or health related subject matter. At some predetermined time, the user may wish to transfer data from the device  226  to another location. 
     As shown in  FIG.  2 B , device  226  may include an input mechanism, such as a depressible input button  228  assist in operation of the device  226 . The input button  228  may be operably connected to a controller  230  and/or any other electronic components, such as one or more of the elements discussed in relation to computer  102  shown in  FIG.  1 B . Controller  230  may be embedded or otherwise part of housing  232 . Housing  232  may be formed of one or more materials, including elastomeric components and comprise one or more displays, such as display  234 . The display may be considered an illuminable portion of the device  226 . The display  234  may include a series of individual lighting elements or light members such as LED lights  234  in an exemplary embodiment. The LED lights may be formed in an array and operably connected to the controller  230 . Device  226  may include an indicator system  236 , which may also be considered a portion or component of the overall display  234 . It is understood that the indicator system  236  can operate and illuminate in conjunction with the display  234  (which may have pixel member  235 ) or completely separate from the display  234 . The indicator system  236  may also include a plurality of additional lighting elements or light members  238 , which may also take the form of LED lights in an exemplary embodiment. In certain embodiments, indicator system may provide a visual indication of goals, such as by illuminating a portion of lighting members  238  to represent accomplishment towards one or more goals. 
     A fastening mechanism  240  can be unlatched wherein the device  226  can be positioned around a wrist of the user  124  and the fastening mechanism  240  can be subsequently placed in a latched position. The user can wear the device  226  at all times if desired. In one embodiment, fastening mechanism  240  may comprise an interface, including but not limited to a USB port, for operative interaction with computer  102  and/or devices  138 ,  140 . 
     In certain embodiments, device  226  may comprise a sensor assembly (not shown in  FIG.  2 B ). The sensor assembly may comprise a plurality of different sensors. In an example embodiment, the sensor assembly may comprise or permit operative connection to an accelerometer (including in the form of a multi-axis accelerometer), heart rate sensor, location-determining sensor, such as a GPS sensor, and/or other sensors. Detected movements or parameters from device&#39;s  142  sensor(s), may include (or be used to form) a variety of different parameters, metrics or physiological characteristics including but not limited to speed, distance, steps taken, and energy expenditure such as calories, heart rate, sweat detection, effort, oxygen consumed, and/or oxygen kinetics. Such parameters may also be expressed in terms of activity points or currency earned by the user based on the activity of the user. 
     I. Illustrative Athletic Monitoring Methods 
     System  100  may prompt a user to perform one or more exercises, monitor user movement while performing the exercises, and provide the user with an energy expenditure estimate based on their movement. System  100  may analyze a user&#39;s form to determine if the user is making an exercise more or less difficult, and adjust the energy expenditure estimate accordingly. Energy expenditure estimates may be, or comprise, an estimate of calories burned by the user. In certain embodiments, energy expenditure determinations may be based on, and/or conveyed as a point system. In one embodiment, calories may be converted to a point system, yet in other embodiments, measurements may be directly obtained in one or more point systems. In one implementation, activity points may be based upon: form, body movements, and/or completion of certain activities. In further embodiments, energy expenditure calculations may comprise determinations relating to: effort, oxygen consumed, and/or oxygen kinetics of the user. In one embodiment, computer  102 , camera  126 , sensor  128 , and display  136  may be implemented within the confines of a user&#39;s residence, although other locations, including gyms and/or businesses are contemplated. Further, as discussed above, computer  102  may be a portable device, such as a cellular telephone, therefore, one or more aspects discussed herein may be conducted in almost any location. In this regard, the example embodiments of this disclosure are discussed in the context of being implemented with one or more of the example components of system  100 . Those skilled in the art will appreciate that reference(s) to a particular component, such as computer  102 , is not meant to be limiting, but rather to provide an illustrative example of one of many possible implementations. Thus, although certain components may be referenced, it is to be assumed that other components of system  100  may be utilized unless expressly disclaimed or physically impossible. Further, aspects disclosed herein are not limited to example system  100 . 
     A. Monitoring User Movements 
     While exercising, the system  100  may use one or more techniques to monitor user movement.  FIG.  3    illustrates an example flow diagram of a method for calculating an energy expenditure estimate for a user that accounts for a user&#39;s form while exercising as part of the estimate, in accordance with example embodiments. The method may be implemented by a computer, such as, for example, computer  102 , device  138 ,  140  and/or  142 , as well as or other apparatuses. The blocks shown in  FIG.  3    may be rearranged, some blocks may be removed, additional blocks may be added, each block may be repeated one or more times, and the flow diagram may be repeated one or more times. The flow diagram may begin at block  302 . 
     1. Perform User Assessment 
     In block  302 , the method may include performing an initial assessment of the user. A user, such as user  124 , may be positioned in range of a sensor, such as in front of the image capturing device  126  and/or sensor  128 , which may comprise an infrared transceiver. Display  136  may present a representation of user  124  that may be a “mirror-image” or depict a virtual avatar, such as a user avatar, that moves to correspond with user movement. Computer  102  may prompt the user to move into a certain region relative to the image capturing device  126  and/or relative to the infrared transceiver  128  so that the user is within frame and/or range. When properly positioned, system  100  may process movement of the user. Although the term “initial” has been utilized, this assessment may occur each time the user initiates system  100 , performs certain movements, upon passage of time, or for any other reason. Thus, references to assessments herein are not limited to a single assessment. 
     a. Identify Sensory Locations 
     System  100  may process sensory data to identify user movement data. In one embodiment, sensory locations on a user&#39;s body may be identified. With reference to  FIG.  4   , sensory locations  402   a - 402   o  may correspond to locations of interest on the user&#39;s  124  body (e.g., ankles, elbows, shoulders, etc.). For example, images of recorded video, such as from camera  126 , may be utilized in an identification of the sensory locations  402   a - 402   o.  For example, the user may stand a certain distance, which may or may not be predefined, from the camera  126 , and system  100  may process the images to identify the user  124  within the video, for example, using disparity mapping techniques. In an example, image capturing device  126  may be a stereo camera having two or more lenses that are spatially offset from one another and that simultaneously capture two or more images of the user. System  100  may process the two or more images taken at a same time instant to generate a disparity map for determining a location of certain parts of the user&#39;s body in each image (or at least some of the images) in the video using a coordinate system (e.g., Cartesian coordinates). The disparity map may indicate a difference between an image taken by each of the offset lenses. 
     In a second example, one or more sensors may be located on or proximate to the user&#39;s  124  body at the sensory locations  402   a - 402   o  or the user  124  may wear a suit having sensors situated at various locations. Yet, in other embodiments, sensor locations may be determined from other sensory devices, such as devices  138 ,  140  and/or  142 . In this regard, sensors may be physical sensors located on a user&#39;s clothing, yet in other embodiments, sensor locations  402   a - 402   o  may be based upon identification of relationships between two moving body parts. For example, sensor location  402   a  may be determined by identifying motions of user  124 . In this regard, the overall shape or portion of a user&#39;s body may permit identification of certain body parts. Regardless of whether a camera, such as camera  126 , is utilized and/or a physical sensor located on the user  124 , such as sensors within device(s)  138 ,  140 ,  142  are utilized, the sensors may sense a current location of a body part and/or track movement of the body part. 
     In certain embodiments, a time stamp may be added to the data collected (such as collected part of block  302  in  FIG.  3   ) indicating a specific time when a body part was at a certain location. Sensor data may be received at computer  102  (or other device) via wireless or wired transmission. A computer, such as computer  102  and/or devices  138 ,  140 ,  142 , may process the time stamps to determine the locations of the body parts using a coordinate system (e.g., Cartesian coordinates) within each (or at least some) of the images in the video. Data received from camera  126  may be corrected, modified, and/or combined with data received from one or more other devices  138 ,  140 , and  142 . 
     In a third example, system  100  may use infrared pattern recognition to detect user movement and locations of body parts of the user  124 . For example, sensor  128  may include an infrared transceiver, which may be part of camera  126 , or another device, that may emit an infrared signal to illuminate the user&#39;s  124  body using infrared signals. The infrared transceiver  128  may capture a reflection of the infrared signal from the body of user  124 . Based on the reflection, the system  100  may identify a location of certain parts of the user&#39;s body using a coordinate system (e.g., Cartesian coordinates) at particular instances in time. Which and how body parts are identified may be predetermined based on a type or types of exercise a user is requested to perform. 
     As part of a workout routine, system  100  may make an initial postural assessment of the user  124  as part of the initial user assessment in block  302  of  FIG.  3   . With reference to  FIG.  5   , system  100  may analyze front and side images of a user  124  to determine a location of one or more of a user&#39;s shoulders, upper back, lower back, hips, knees, and ankles. On-body sensors and/or infrared techniques may also be used, either alone or in conjunction with camera  126 , to determine the locations of various body parts for the postural assessment. For example, system  100  may determine assessment lines  124   a - g  and/or regions  502 - 512  to determine the locations of a various points on a user&#39;s body, such as, for example, ankles, knees, hips, upper back, lower back, and shoulders. 
     b. Identify Sensory Regions 
     In further embodiments, system  100  may identify sensory regions (see, e.g., block  302 ). 
     In one embodiment, assessments lines  124   a - g  may be utilized to divide the user&#39;s body into regions. For example, lines  124   b - f  may be horizontal axes. For example, a “shoulders” region  502  may correlate to a body portion having a lower boundary around the user&#39;s shoulders (see line  124   b ), region  504  may correlate to the body portion between the shoulders (line  124   b ) and about half the distance to the hips (see line  124   c ) and thus be an “upper back” region, and region  506  may span the area between line  124   c  to the hips (see line  124   d ) to comprise a “lower back region.” Similarly, region  508  may span the area between the “hips” (line  124   d ) and the “knees” (see line  124   e ), region  510  may span between lines  124   e  and  124   f  and region  512  (see “ankles”) may have an upper boundary around line  124   f  Regions  502 - 512  may be further divided, such as into quadrants, such as by using axes  124   a  and  124   g.  To aid in the identification of one or more sensory regions, system  100  may prompt the user to make one or more specific movements. For example, system  100  may prompt a user to move a specific body part or region (e.g., waive their right arm, or waive the left arm in a specific pattern) to aid the system  100  (e.g., computer algorithm processing information received from the infrared transceiver  128 ) in determining which body part or region is in a specific location within a coordinate system. 
     c. Categorize Locations or Regions 
     In certain embodiments, body parts or regions that are not proximate to each other may nonetheless be categorized into the same movement category (see, e.g., block  302 ). For example, as shown in  FIG.  5   , the “upper back”, “hips”, and “ankles” regions  504 ,  508 ,  512  may be categorized as belonging to a “mobility” category. In another embodiment, the “lower back” and “knees” regions  506 ,  510  may be categorized as belonging to a “stability” category. The categorizations are merely examples, and in other embodiments, a location or region may belong to multiple categories. For example, a “center of gravity” region may be formed from regions  504  and  506 . In one embodiment, a “center of gravity” may comprise portions of regions  504  and  506 . In another embodiment, a “center of moment” category may be provided, either independently, or alternatively, as comprising a portion of at least another category. In one embodiment, a single location may be weighted in two or more categories, such as being 10% weighted in a “stability” category and 90% weighted in a “mobility” category. 
     System  100  may also process the image to determine a color of clothing of the user or other distinguishing features to differentiate the user from their surroundings. After processing, system  100  may identify a location of multiple points on the user&#39;s body and track locations of those points, such as locations  402  in  FIG.  4   . System  100  may also prompt the user to answer questions to supplement the postural assessment, such as, for example, age, weight, etc. Again, block  302  is optional and is not required in accordance with various embodiments. 
     2. Providing Form 
     With reference again to  FIG.  3   , in block  304 , various embodiments may include demonstrating proper form for an exercise and prompting the user to perform the exercise. For example, after or in addition to the initial postural assessment, the system  100  (such as with computer  102 ) may cause the display  136  to present a virtual trainer demonstrating an exercise to instruct the user on proper form and/or may present a depiction and/or an actual video of a real person demonstrating proper form for an exercise. System  100  may then prompt the user to begin performing the exercise. 
     With reference to  FIG.  3   , in block  306 , various embodiments may include monitoring form of a user performing the exercise. As seen in  FIG.  6   , system  100 , such as through computer  102 , may cause the display  136  to present a virtual avatar  602  of the user. The virtual avatar  602  may move in synchronism with the user  124 . Also, the display  136  may present video of the actual user, rather than avatar  602 . System  100  may process one or more frames in the video to determine at least some of the sensory locations  402 , or may receive data from sensors worn on-body by the user. As shown in  FIG.  6   , sensory locations  402  may be displayed on the virtual avatar. 
     For proper form during many exercise routines, a user may proceed through multiple positions during a repetition of an exercise. Certain aspects disclosed herein relate to defining one or more measurement positions and/or desired locations for one or more sensory locations  402 . For example, a measurement position may refer to a particular relationship between various body parts during a repetition. For example, a measurement position may indicate a desired location for a user&#39;s body part (e.g., desired location of user&#39;s left elbow) and may indicate a desired relationship between multiple body parts (e.g., angle between a user&#39;s torso and thigh). For a movement or series of movements (such as an exercise routine), system  100  may define one or more measurement positions and/or desired locations for one or more of the sensory locations  402  for a measurement position. In various implementations, each repetition of an exercise can be broken down into one or more measurement positions. 
     System  100 , such as through computer  102 , may process video or sensor data of a user performing an exercise to determine when a user&#39;s body has reached a measurement position. For each measurement position, system  100  may compare the measured sensory locations to desired sensory locations to monitor the user&#39;s form while performing the exercise. For example, frame  1  of  FIG.  6    may correspond to a first measurement position and frame  2  may correspond to a second measurement position. System  100  may determine a distance between sensory locations  402   c  and  402   d  at each measurement position. Other relationships between sensory locations may be specified (e.g., certain angle, certain position, etc.) 
     With reference again to  FIG.  3   , in block  308 , various embodiments may include calculating an energy expenditure estimate for the user. Calculations may be based on a type of the exercise and/or on the form of the user. The energy expenditure estimate may be, or comprise, for example, an estimate of calories burned by the user. In certain embodiments, energy expenditure calculations comprise determinations relating to: effort, oxygen consumed, and/or oxygen kinetics of the user. During a workout session or upon its completion, the system  100  may inform the user of energy expended. In one embodiment, system  100  may provide an indication of a quantity of calories they have burned. To provide a more accurate calories burned estimate, system  100  may account for a user&#39;s form while performing an exercise as well as the type of exercise that was performed. Further embodiments may utilize user attributes to more accurately identify a number of calories burned by a user. Example user attributes may be height, weight, age, etc. One or more sensors may determine the user attributes, or the user may input the user attributes via an interface to a computer, such as computer  102 . 
     System  100  may use information from sensory locations  402  detected at measurement positions of an exercise in combination with one or more known values to obtain a more accurate determination of calories burned. In one embodiment, a known value may comprise or be part of a Metabolic Equivalent of Task (MET) table. A MET table, for example, may be defined for a particular exercise (e.g., squat, lunge, etc.) and used to determine how many calories a user burned during a workout. System  100  may store or have access to multiple MET tables corresponding to different exercises (e.g., squat, lunge, jumping rope, push up, running, etc.). System  100  may process data from the video and/or sensors to determine a number of repetitions of an exercise that a user has performed or duration of an exercise, and may estimate a number of calories burned by the user based on the repetitions and/or duration information and the one or more known values, such as may be obtained from MET tables. 
     MET tables, however, are statistical averages and are not as accurate as they could be. Thus, conventional calorie measurement systems that rely on MET tables merely provide a user with a rough estimate of how many calories they burned during a workout. Although embodiments of this disclosure may utilize one or more values from a MET table, aspects of this disclosure are not limited by the deficiencies of prior measurements systems. For example, in one embodiment the user&#39;s form may be accounted for. System  100  may apply a scaling factor to a calories burned estimate based on detected sensory location information. The scaling factor may reflect how well a user has performed an exercise and in certain embodiments may consider attributes of the user. For example, the scaling factor may be a function of one or more of the sensory location information, a duration during which the user performed an exercise, information reported by the user (e.g., age, weight), a user&#39;s heart rate taken by a heart rate monitor, a pressure measurement, and/or other data. A pressure measurement may be obtained from pressure sensor  140  located in a shoe, for example, to determine how much force a user exerts during movement. For example, a user may be holding a weight in each hand and the pressure sensor  140  may monitor pressure at the shoe. The pressure sensor  140  may also indicate how quickly a user changes direction (e.g., how hard a user made a cut) or how much power was exerted when jumping. 
     To determine the scaling factor, system  100  may monitor for relationships between one or more body parts at one or more measurement positions during a repetition of an exercise. Modifications to these relationships may make an exercise easier or harder to perform. The scaling factor may consider factors indicative of whether a user is making the exercise more or less difficult to complete, and may adjust a calories burned estimate accordingly. In a squat, for example, relationships may be defined for a first angle between a user&#39;s torso and thighs, and a second angle between a user&#39;s thighs and shin while performing the squat. System  100  may process sensory location information to measure the first and second angle of the user over time for comparison with the desired first and second angle. 
     In an example, with reference to  FIGS.  7 A-B , a virtual avatar  702  of a user is displayed performing a squat. Virtual avatar  702  is depicted as a stick figure, and proper technique for an exercise is shown as a shaded region  704 . At the lowest part of the squat (for example, as shown in  FIG.  7 A ), the desired form may specify a relationship between a user&#39;s thigh and shin, between a user&#39;s back and arms, and/or any other two parts or locations the user. In one embodiment, the desired form may specify a first predetermined angle between a location or part. For example, a user&#39;s upper leg and lower leg, and/or a second predetermined angle between a user&#39;s back and arms. System  100  may process the sensory location information to compare the user&#39;s form to the desired form. For example, system  100  may process the sensory location information to determine an angle between the user&#39;s thigh and shin, and an angle between the user&#39;s back and arms when performing a squat. 
     System  100  may define thresholds for the relationships between various body parts for adjusting the scaling factor. The thresholds may permit the user&#39;s form to differ by a certain amount from the desired form. For a preferred threshold, system  100  may determine that the user has good form that does not require any adjustment of the scaling factor (e.g., less than a 5% difference between angle between the user&#39;s upper leg and lower leg and desired angle). For an acceptable threshold, the system  100  may nominally adjust the scaling factor upward or downward to reflect increased or reduced effort by the user (e.g., 5-15% difference between angle between the user&#39;s upper leg and lower leg and desired angle). For an unacceptable threshold, the system  100  may determine that the user&#39;s form has reduced the amount of effort to perform the exercise and may downwardly adjust the scaling factor (e.g., greater than a 15% difference between angle between the user&#39;s upper leg and lower leg and desired angle). 
     System  100  may also adjust the scaling factor based on omissions or additions a user makes when performing an exercise. For example, a user may not be doing an arm movement in an exercise that requires movement of both arms and legs. Also, if the user is performing an additional movement beyond what is specified for an exercise, the system  100  may adjust the scaling factor to increase the calorie estimate. 
     Upon determining the scaling factor, the system  100  may determine an amount of calories burned as a function of the scaling factor(s) and the calorie estimate. The function may be a multiplication of the calorie estimate by the scaling factor, or via other relationships. For example, the scaling factor may be adjustments to a number of variables in a mathematical equation for adjusting calories burned by one or more of multiplication, addition, and subtraction. In further embodiments, system  100  may cease determinations relating to caloric expenditure if the user deviates from a threshold. For example, a user may be interrupted during a workout routine and either forget or be too distracted to “pause” the determination, thus, certain embodiments may cease determining caloric expenditure upon detecting that a user is not performing an exercise. Further embodiments may cease or otherwise alter determinations of caloric expenditure if one or more variation thresholds are exceeded, such as for example, if a user is over-extending or under-extending a body region or part. In certain embodiments, if a user&#39;s movements are prone to cause injury, measurements and/or determinations relating to caloric expenditure may be stopped. In one implementation, system  100  may provide cues and/or instructions to correct the user&#39;s deficiencies or incorrect movements. 
     The following provides an example equation for calculating an amount of calories burned by a user during a workout. 
       Calories burned=BMR*(Activity modifier)*(Completeness modifier).  Equation (1)
 
     In equation (1), BMR is an acronym for Basal Metabolic Rate. The system  100  may calculate the BMR using the Mifflin-St. Jeor Equation, BMR=(10*w)+(6.25*h)−(5.0*a)+(5 for men, −161 for women), where “*” is the multiplication symbol, “w”=weight in kilograms, “h”=height in centimeters, “a”=age in years. The system  100  may also use the Harris-Benedict equation instead of or, in addition to, the Mifflin-St. Jeor Equation. 
     The activity modifier may be an adjustment corresponding to a type of exercise being performed by a user. The activity modifier may be larger for more strenuous exercises, and smaller for less strenuous. System  100  may store a file containing activity modifiers, where each activity modifier may have a value for a particular exercise type. Two or more exercises may have activity modifiers with a same value, or certain exercise may have a unique value for the activity modifier. The activity modifier may have a default value. In one example embodiment, the default value may be 0.1. In a second embodiment, the default value may be 1.0. The default value may be any value, including 0.0. System  100  may update the default value to correspond to the activity modifier for an exercise currently being performed by the user. Over a duration of the workout, system  100  may use different ones of the activity modifiers to calculate calories burned using equation (1) corresponding to different exercises the user is prompted to perform. One or more factors may contribute to the activity modifier and/or adjustment of the modifier. Examples include, but are not limited to: pace, type of exercise, duration, and combinations thereof. Further, activity modifiers and/or variation of activity modifiers may be determined from predetermined values (such as a value assigned to an exercise or movement that a user is prompted to perform), the user&#39;s performance, information from a MET table on a particular exercise, and combinations thereof. 
     The completeness modifier may be used for adjusting the BMR based on how well a user&#39;s form corresponds to a desired form when performing an exercise. In an example, the completeness modifier may indicate what percentage of full movement was achieved for each repetition when performing an exercise (e.g., determine a percentage of a measured angle between the user&#39;s torso and thighs for a particular repetition of an exercise relative to a desired angle), or may be an average of the percentage of full movement for a predetermined number of repetitions (e.g., last three exercises, last five exercises, all exercises, etc.). The completeness modifier may have a default value. In one example embodiment, the default value may be 0.1. In a second embodiment, the default value may be 1.0. The default value may be any value, including 0.0. System  100  may update the completeness modifier over time based on how well the user&#39;s form conforms to a desired form. One or more factors may contribute to the activity modifier and/or adjustment of the modifier. Examples include, but are not limited to: pace, type of exercise, duration, and combinations thereof. Further, activity modifiers and/or variation of activity modifiers may be determined from predetermined values (such as a value assigned to an exercise or movement that a user is prompted to perform), the user&#39;s performance, and combinations thereof. 
     Equation (2), provided below, may be utilized in further embodiments. 
       Calories burned=BMR*(Activity modifier)*(Completeness modifier)*(Multiply Modifier)+(Addition Modifier)  Equation (2)
 
     Values for BMR, Activity Modifier, and/or Completeness Modifier of Equation (2) may be determined in accordance with one or more embodiments described above in reference to Equation (1). In one embodiment, the value of the Multiply Modifier may be defined for each type of exercise. In one example embodiment, the default value may be 0.1. In a second embodiment, the default value may be 1.0. The default value may be any value, including 0.0. System  100  may update the Multiply Modifier during a workout to correspond to a type of exercise the user is prompted to perform. In certain embodiments, the Activity Modifier may be obtained (either partially or entirely) from empirical data. 
     In certain embodiments, the value of the Addition Modifier may be defined for each type of exercise. In one example embodiment, the default value may be 0.1. In a second embodiment, the default value may be 1.0. The default value may be any value, including 0.0. System  100  may update the Addition Modifier during a workout to correspond to a type of exercise the user is prompted to perform. In certain embodiments, the Activity Modifier may be obtained (either partially or entirely) from empirical data. 
     System  100  may calculate the calories burned over a duration of a workout, which may incorporate the utilization of equations (1) or (2). System  100  may cause the display  136  to display a running total of calories burned. In certain embodiments, the total may be determined for one or more completed repetitions and one or more completed sets of each exercise. System  100  may also calculate and cause display of calories burned by type of exercise performed. Other information such as, for example, peak/minimum/average calorie burning rate by workout, by repetition, by set, or by exercise type may also be calculated and displayed. System  100  may periodically determine an amount of calories burned by the user while exercising using equation (1). System  100  may indicate a current amount of calories burned that is continually updated over a workout (e.g., a running total), or may update the calories burned amount at predetermined times (e.g., user completes a set of a first type of exercise and begins a set of second type of exercise, at the end of the workout session, etc.). System  100  may also inform the user how many calories were burned during each repetition as well as in each set of an exercise. 
     One or more of the inputs and/or variables used in the determination of caloric expenditure (such as with equation (1)) may remain the same regardless of the type of exercise being performed by the user, yet others may vary. For example, the BMR may be the same over the entire workout as a user&#39;s weight, height, and age do not change appreciably over the course of a workout. Further, one or more of the Activity modifier, Completeness modifier, Multiply Modifier, and Addition Modifier may vary over the workout. The values (and/or variation) of the values may depend on the type exercise currently being performed by the user. 
     The Completeness modifier may vary from repetition to repetition. As noted above, system  100  may generate the Completeness modifier based on monitoring a user&#39;s form while they perform an exercise. Generally, an exercise includes a sequence of motions to perform one repetition, and a user typically performs a set that includes two or more repetitions. A user&#39;s form may vary from repetition to repetition, and so may the Completeness modifier. 
     System  100  may determine calories burned using equation (1) based on a Completeness modifier that varies from repetition to repetition, or based on a filtered version of the Completeness modifier. To filter the Completeness modifier, the system  100  may, for example, determine a Completeness modifier for one or more repetitions, may average some or all of the Completeness modifiers, and may use the average in equation (1). Also, system  100  may generate the Completeness modifier as a weighted average, where Completeness modifiers of some repetitions may be given greater weight than others. For example, system  100  may apply a decaying function where more recent Completeness modifiers are weighted more heavily than less recent when generating an average. 
     System  100  may also allow a user to make desired movements, and calculate an amount of calories burned for such movement. In one embodiment, all detected movements may be utilized in calculations. Yet in other embodiments, only certain (e.g., system supported and/or those prompted to be performed) movements may be considered. System  100  may process data from image capturing device  126  and/or from various sensors to attempt to classify a user&#39;s movement. For example, system  100  may compare the user&#39;s movement to other known movements for which a MET table has been defined. If a user&#39;s movement corresponds to a known movement for which a MET table has been defined, then system  100  may use the identified MET table for calculating an amount of calories burned. 
     If the user&#39;s movement does not match an exercise defined by a MET table, the system  100  may identify one or more exercises that include movements similar to the movement being performed by the user. For example, system  100  may determine that the user&#39;s lower body moves similar to a squat and upper body moves similar to a pushup. System  100  may calculate the number of calories the user would burn using the identified MET tables as if the users were doing a squat, and as if they were doing a pushup, as approximations for the amount of calories burned by the user. In further embodiments, a new entry may be created. In this regard, certain embodiments may permit the entry and later identification of new movements and/or exercises. In certain embodiments, the user may provide inputs regarding an approximate caloric expenditure for an unidentified movement/exercise. Yet in other embodiments, system  100  may calculate caloric expenditure, such as from one or more sensors as discussed herein. In still yet further embodiments, system  100  may utilize one or more sensor readings as well as an input from a user (and/or third-party) in determining attributes, such as caloric expenditure, for previously unknown movements or exercises. Examples of estimating caloric expenditure without MET tables, may include but are not limited to, determining changes in potential energy. Examples of using changes in potential energy are provided in the next section. 
     System  100  may be configured to transmit calories burned estimates to a social networking website. The users may be ranked based on their total number of calories burned for a desired time interval (e.g., rank by day, week, month, year, etc.). With reference again to  FIG.  3   , the method may end or may return to any of the preceding blocks. 
     i. Energy Expenditure Estimate based on Changes in Potential Energy 
     System  100  may also calculate an energy expenditure estimate of a user for physical activities not defined by a MET table. For example, system  100  may calculate an amount of calories burned by a user performing any desired combination of movements. During a workout, a user may be exposed to their own body weight and gravity. A location of a user&#39;s center of mass, or of a center of mass of a particular body part, may be utilized in estimating an amount of calories burned by the user performing an athletic activity. 
       FIG.  8    illustrates an example flow diagram of a method for calculating an energy expenditure estimate for a user while performing an athletic activity based on monitoring changes in potential energy, in accordance with example embodiments. The method may be implemented by a computer, such as, for example, computer  102 , device  138 ,  140  and/or  142  as well as other apparatuses. The blocks shown in  FIG.  8    may be rearranged, some blocks may be removed, additional blocks may be added, each block may be repeated one or more times, and the flow diagram may be repeated one or more times. The flow diagram may begin at block  802 . 
     In block  802 , various embodiments may involve processing data captured of a user performing an athletic activity over a time interval. In an example, system  100  may prompt a user to perform ten repetitions of a lunge and may process data captured of the user performing the lunge. The data may be video captured by the camera  126  or may be captured by the infrared transceiver  128 , and/or by the other device sensors  138 ,  140 , and  142 . 
     In block  804 , various embodiments may involve determining a location of a center of mass of a body part, body region, or of an entire body of the user at a first time instant and at a second time instant within the time interval. Yet in other embodiments, a center of movement may be utilized. For simplicity purposes, however, a center of mass will be discussed. In an example, system  100  may instruct the user to place sensors at locations of corresponding to a center of mass for one or more body parts of the user. With reference to  FIG.  9   , one or more of center of mass locations may be at example locations  904 A-D and  906 , or at other locations on the user&#39;s body. Any number of locations may be monitored. At least one sensor may wirelessly transmit sensor data indicating a time and a location of the sensor (or location of a body part as detected by the sensor). A location may be coordinates in a coordinate system (e.g., Cartesian coordinate system) and may be associated with a time stamp indicating when the sensor was at a particular coordinate. In certain embodiments, system  100  may process the sensor data to periodically determine locations  904 A-D and  906 . For example, system  100  may receive sensor data, such as from device sensors  138 ,  140  and/or  142 . Computer  102  (or another component of system  100 ) may process data as part of determining locations (such as locations  904 A-D and  906 ). In one embodiment, data may be processed on a routine ongoing-basis, such as four times per second. In another example, computer  102  (or another component of system  100 ) may process data from image capturing device  126  to determine locations  904 A-D and/or  906 . 
     In block  806 , various embodiments may involve identifying a change in the location of the center of mass from the first time instant to a second time instant. As discussed above, system  100  may determine locations  904 A-D and  906  at one time and at a subsequent time. For example and with reference to  FIGS.  10 A-B , a user is shown performing a lunge.  FIG.  10 A  corresponds to a first time instant and  FIG.  10 B  corresponds to a second time instant. In  FIG.  10 A , a location  906  of a user&#39;s center of mass is at a height “h 1 ” (designated by  908 A) off of the ground. In  FIG.  10 B , a location  906  of a user&#39;s center of mass is at a height “h 2 ” (designated by  908 A) off of the ground. One or more components of system  100  may determine a difference between height “h 1 ” and “h 2 ” to determine a change in a location  906  of the center of mass. System  100  may also calculate changes to locations  904 A-D of centers of mass for other body parts, or changes to other locations of body parts or body regions of the user. System  100  may also process video of a user taken from different angles, as shown in  FIG.  11   , to determine locations  904 A-D and  906 . For example, system  100  may determine height “h 1 ” for location  906  in a perspective view and height “h 2 ” for location  906  in a front view of the user. System  100  may average the different height measurements, or may use one or the other. 
     With reference again to  FIG.  8   , in block  808 , various embodiments may calculate an energy expenditure estimate for the user due to the change. In an example, the physics concept of potential energy may be used to estimate the amount of work done by the user, and to calculate calories burned based on work. 
     In an example, one or more components of system  100  may determine changes of a location  906  from one time instant to another to determine an amount of work performed by the user. Potential Energy (PE)=m*g*h, where m=mass of the user (or body part), g=the acceleration due to gravity, and h=height above ground. Work (W)=−ΔPE, where Δ is represents a change in potential energy. Substituting m*g*h, Work (W)=−m*g*Δh. Based on the above example in  FIGS.  10 A-B , W=−m*g* (h 1 −h 2 ). System  100  may determine an amount of calories burned as a function of work multiplied by physiology of human efficiency. System  100  may determine the amount of calories burned based on the amount of work and a physiology of human efficiency (PHE) scaling factor. The system  100  may determine the PHE scaling factor as a function of one or more of the user&#39;s heart rate, pressure sensor data, and other information input by the user (e.g., age, weight, etc.) 
     System  100  may keep and/or transmit a running total of calories burned between subsequent time instants and inform the user of a total amount of calories burned up to that point in an exercise session. For example, system  100  may determine a height h of location  906  at a certain frequency (e.g., 2 times per second), and may calculate calories burned based on a difference in calories burned between each determination of height h. The system  100  may also track a total number of calories burned over a predetermined time range covering one or more workouts. A time range may include a week, month, year, cumulative time since a user began working out, or other defined metrics. One or metrics may comprise default values, predefined values, user-selectable values, and/or user-defined values. For example, system  100  may inform the user of how many calories they have burned during a specified time period, such as a day, week, month, and/or year. System  100  may also maintain data on average number of calories burned per workout, average number of calories burned based on a type of workout, a greatest number of calories burned during a single workout or during a predetermined time interval (e.g., month where highest amount of calories were burned), or other types of data. 
     In another example, system  100  may determine calories burned by movement of a particular body part or by a collection of body parts. For instance, a user may desire to know how many calories were burned by movement of their right leg. Using the above relationship between work and potential energy, and with reference again to  FIG.  9   , system  100  may monitor changes in the location  904 A of the center of mass of the user&#39;s right leg (e.g., height  908 B) from one time instant to a different time instant to calculate work. System  100  may estimate the mass of the user&#39;s right leg based on the user&#39;s weight and proportions. System  100  may then determine an amount of calories burned as a function of work multiplied by physiology of human efficiency, as described above. During an exercise session, system  100  may display, such as through display  136 , a running total of calories burned attributable to movement of the user&#39;s right leg. System  100  may similarly determine calories burned based on locations  904 B-D for the other limbs of the user. During an exercise session, system  100  may display a running total of calories burned by a user&#39;s entire body, as well by each limb. 
     System  100  may also permit a user to review an exercise session to determine how many calories were burned at certain times. For example, an exercise may involve performing repetitive motions (e.g., pushups). System  100  may identify each repetition within a set (e.g., each pushup within a set of 10), as well as a number of calories burned during each repetition. Over a set, one or more components of system  100  may identify the repetition where the user burned a highest number of calories as well as a lowest number of calories. In further embodiments, system  100  may estimate an average number of calories. These are merely exemplary statistics and those skilled in the art will readily appreciate that other analysis may be conducted without departing from the scope of this disclosure. 
     If an exercise session involves different types of exercises, system  100  may rank the exercise types based on the amount of calories burned by type. For example, an exercise session may involve 3 different types of exercises (e.g., pushups, sit-ups, squats). After completing the exercise session, system  100  may determine how many calories were burned by each exercise type (e.g., 10 calories for pushups, 13 calories for sit-ups, and 18 calories for squats), and rank the exercise types based on the number of calories burned (e.g., first squats, second sit-ups, third pushups). In further embodiments, energy expenditure (e.g., a quantity of calories burned) may be ranked as percentage over an ideal value or range for an exercise or routine. For example, if perfectly performing an exercise would burn about 100 calories, a first user who burned 90 calories may be assigned a better ranking than second user who only burned 85 for the same exercise. The users could have different ideal values or ranges, thus the determinations may utilize the percentage of the detected and/or estimated values as a percentage for that user&#39;s ideal value. In further embodiments, a user who is closer to 100% of their ideal value may be ranked higher than users who have over 100% of the ideal quantity of calories burned. In this regard, a user who expends more energy than estimated or calculated for an activity (e.g., exercise) may indicate improper movements, inefficiency, increased likelihood of injury, and/or combinations thereof. In certain implementations, the method of  FIG.  8    may then end, or may return to any of the preceding blocks and/or other processes. 
     System  100  may also determine calories expended from pre-recorded videos. For example, a user may upload video of a professional basketball player dunking a basketball to system  100 . One or more components of system  100  may process the video to determine locations of a center of mass of the player, or of particular body parts, at various points in time, and determine the amount of calories expended during the physical activity (e.g., by the player during the dunk) using the work-based calorie determination, described above. 
     In various embodiments of the invention energy expenditure may be calculated with multiple sensors. Some of the calculation may be independent of other calculations. For example, a user may perform an exercise while wearing a wrist worn sensor and while being observed by a camera based sensor system. The wrist worn sensor and the camera based system may independently calculate energy expenditure values. When two or more independent systems are utilized, different energy expenditure values may be calculated. 
     In some embodiments of the invention energy expenditure values are used to award points to users. When multiple sensors or systems of sensors are used to independently calculate energy expenditure, users may receive points for each sensor or system of sensors that calculates energy expenditure. Alternative, one energy expenditure value may be determined based on one of calculated values or some combination of the calculated values. For example, prior to beginning an exercise a user may select the sensor or sensor systems that will be used to calculate energy expenditure. Alternatively, a system may select the sensor or sensor system that will be used. The selection may be based on the accuracy in calculating energy expenditure for all of the available sensors or sensor systems. The selection and accuracy may be functions of the exercise that will be performed. For example, a first sensor may result in more accurate energy expenditure calculations while a user is running and a second sensor may result in more accurate energy expenditure calculations while a user is performing squats. Other embodiments may include using an average, a weighted average or a statistical solution to determine energy expenditure. 
     In addition to using multiple independent sensors and sensor systems for calculating energy expenditure, some embodiments of the invention may utilize multiple display devices for displaying energy expenditure or energy expenditure point values. When one sensor or sensor system is used to calculate energy expenditure, the display device associated with the sensor or sensor system that is not used may be disabled. Alternative, the display device associated with the sensor or sensor system that is not used may be driven by the sensor or sensor system that is used. For example, a wrist worn sensor system and a camera based system may both include displays for displaying energy expenditure. When both systems are available and the camera based system is selected to calculate energy expenditure, the camera based system may provide data to the wrist worn sensor system so that the display associated with the wrist worn sensor system displays the same values as the display associated with the camera based system. Similarly, when combinations of multiple independent sensor or sensor systems are used to calculate energy expenditure, the displays associated with each sensor or sensor system may be driven to display the same data. 
     II. Illustrative Methods for Combining Energy Expenditure Estimates 
     A. Illustrative Networks 
     Aspects of this disclosure relate to systems and methods that may be utilized across a plurality of networks. In this regard, certain embodiments may be configured to adapt to dynamic network environments. Further embodiments may be operable in differing discrete network environments.  FIG.  12    illustrates an example of a personal training system  1200  (e.g., system  100  of  FIG.  1   ) in accordance with illustrative embodiments. Example system  1200  may include one or more interconnected networks, such as the illustrative body area network (BAN)  1202 , local area network (LAN)  1204 , and wide area network (WAN)  1206 . As shown in  FIG.  12    one or more networks (e.g., BAN  1202 , LAN  1204 , and/or WAN  1206 ), may overlap or otherwise be inclusive of each other. Those skilled in the art will appreciate that the illustrative networks  1202 - 1206  are logical networks that may each comprise one or more different communication protocols and/or network architectures and yet may be configured to have gateways to each other or other networks. For example, each of BAN  1202 , LAN  1204  and/or WAN  1206  may be operatively connected to the same physical network architecture, such as cellular network architecture  1208  and/or WAN architecture  1210 . For example, portable electronic device  1212  (e.g., device  138 ), which may be considered a component of both BAN  102  and LAN  104 , may comprise a network adapter or network interface card (NIC) configured to translate data and control signals into and from network messages according to one or more communication protocols, such as the Transmission Control Protocol (TCP), the Internet Protocol (IP), and the User Datagram Protocol (UDP) through one or more of architectures  1208  and/or  1210 . These protocols are well known in the art, and thus will not be discussed here in more detail. 
     Network architectures  1208  and  1210  may include one or more information distribution network(s), of any type(s) or topology(s), alone or in combination(s), such as for example, cable, fiber, satellite, telephone, cellular, wireless, etc. and as such, may be variously configured such as having one or more wired or wireless communication channels (including but not limited to: WiFi®, Bluetooth®, Near-Field Communication (NFC) and/or ANT technologies). Thus, any device within a network of  FIG.  12   , (such as portable electronic device  1212  or any other device described herein) may be considered inclusive to one or more of the different logical networks  1202 - 1206 . With the foregoing in mind, example components of an illustrative BAN and LAN (which may be coupled to WAN  1206 ) will be described. 
     1. Example Local Area Network 
     LAN  1204  may include one or more electronic devices, such as for example, computer device  1214 , such as the computer device  102  discussed above in reference to  FIG.  1 A . Computer device  1214 , or any other component of system  1200 , may comprise a mobile terminal, such as a telephone, music player, tablet, netbook or any portable device. In other embodiments, computer device  1214  may comprise a media player or recorder, desktop computer, server(s), a gaming console, such as for example, a Microsoft® XBOX, Sony® Playstation, and/or a Nintendo® Wii gaming console. Those skilled in the art will appreciate that these are merely example of devices for descriptive purposes and this disclosure is not limited to any console or computing device. 
     Those skilled in the art will appreciate that the design and structure of computer device  1214  may vary depending on several factors, such as its intended purpose. One illustrative implementation of computer device  1214  is discussed above in reference to  FIG.  1 B . In some cases, the system of  FIG.  1 B  may be applicable to any device disclosed herein. In some cases, the computer device  1214  (e.g., the computer device  102 ) may include one or more processors, such as processor unit  106 . In some cases, two or more processors may communicate with each other or other components via an interconnection network or bus. The processor unit  106  may include one or more processing cores, which may be implemented on a single integrated circuit (IC) chip. In some cases, the cores may include a shared cache and/or a private cache. One or more caches may locally cache data stored in a system memory (e.g., system memory  108 ), for faster access by components of the processor unit  106 . The system memory  108  may be in communication with one or more processors via a chipset. The cache may be part of system memory  108  in certain embodiments. 
     In some cases, the computing system may include one or more I/O devices (e.g., input devices  120 , output devices  122 , etc.). I/O data from one or more I/O devices  120 ,  122  may be stored at one or more caches and/or system memory  108 . Each of I/O devices  120 ,  122  may be permanently or temporarily configured to be in operative communication with a component of system  100  using any physical or wireless communication protocol via a communication circuit. In some cases, the communication circuit may include a chipset associated with one or more communication protocols, and/or may include one or more discrete components. 
     Returning to  FIG.  12   , four example I/O devices, shown as elements  1216 - 1222 , are shown as being in communication with computer device  1214 . Those skilled in the art will appreciate that one or more of devices  1216 - 1222  may be stand-alone devices or may be associated with another device besides computer device  1214 . For example, one or more I/O devices may be associated with or interact with a component of BAN  1202 , LAN  1204 , and/or WAN  1206 . I/O devices  1216 - 1222  may include, but are not limited to athletic data acquisition units, such as for example, sensors (e.g., image-capturing device  126  and/or sensor  128 ). In further embodiments, I/O devices  1216 - 1222  may be used to provide an output (e.g., audible, visual, or tactile cue) and/or receive an input, such as a user input from athlete  124 . Example uses for these illustrative I/O devices are provided below, however, those skilled in the art will appreciate that such discussions are merely descriptive of some of the many options within the scope of this disclosure. Further, reference to any data acquisition unit, I/O device, or sensor is to be interpreted disclosing an embodiment that may have one or more I/O device, data acquisition unit, and/or sensor disclosed herein or known in the art (either individually or in combination). 
     Information from one or more devices (across one or more networks) may be used to provide (or be utilized in the formation of) a variety of different parameters, metrics or physiological characteristics including but not limited to: motion parameters, such as speed, acceleration, distance, steps taken, direction, relative movement of certain body portions or objects to others, or other motion parameters which may be expressed as angular rates, rectilinear rates or combinations thereof, physiological parameters, such as calories, heart rate, sweat detection, effort, oxygen consumed, oxygen kinetics, and other metrics which may fall within one or more categories, such as: pressure, impact forces, information regarding the athlete, such as height, weight, age, demographic information and combinations thereof. 
     System  1200  may be configured to transmit and/or receive athletic data, including the parameters, metrics, or physiological characteristics collected within system  1200  or otherwise provided to system  1200 . As one example, WAN  1206  may include a server  1211 . The server  1211  may have one or more components illustrated in  FIG.  1 B . Server  1211  may be configured to store computer-executable instructions on a non-transitory computer-readable medium. The instructions may comprise athletic data, such as raw or processed data collected within system  1200 . System  1200  may be configured to transmit data, such as energy expenditure points, to a social networking web site or host such a site. Server  1211  may be utilized to permit one or more users to access and/or compare athletic data. As such, server  1211  may be configured to transmit and/or receive notifications based upon athletic data or other information. 
     Returning to LAN  104 , computer device  1214  is shown in operative communication with a display device  1216  (e.g., display device  136 ), an image-capturing device  1218  (e.g., image capturing device  126 ), sensor  1220  (e.g., sensor  128 ) and/or exercise device  1222 . In one embodiment, display device  1216  may provide audio-visual cues to athlete  124  to perform a specific athletic movement. The audio-visual cues may be provided in response to computer-executable instruction executed on computer device  114  or any other device, including a device of BAN  102  and/or WAN. In one embodiment, data may be obtained from image-capturing device  1218  and/or other sensors, such as sensor  1220 , which may be used to detect (and/or measure) athletic parameters, either alone or in combination with other devices, or stored information, as discussed above. 
     Element  1230  of  FIG.  12    shows an example sensory location (e.g., sensory location  144 ) which may be associated with a physical apparatus, such as a sensor, data acquisition unit, or other device. Yet in other embodiments, it may be a specific location of a body portion or region that is monitored, such as via an image capturing device (e.g., image capturing device  1218 ). In certain embodiments, element  1230  may comprise a sensor, such that elements  1230   a  and  1230   b  may be sensors integrated into apparel, such as athletic clothing. Such sensors may be placed at any desired location of the body of user  124 . Sensors  1230   a/b  may communicate (e.g., wirelessly) with one or more devices (including other sensors) of BAN  1202 , LAN  1204 , and/or WAN  1206 . 
     In one embodiment, exercise device  1222  may be any device configurable to permit or facilitate the athlete  124  performing a physical movement, such as for example a treadmill, step machine, etc. There is no requirement that the device be stationary. In this regard, wireless technologies permit portable devices to be utilized, thus a bicycle or other mobile exercising device may be utilized in accordance with certain embodiments. Those skilled in the art will appreciate that equipment  1222  may be or comprise an interface for receiving an electronic device containing athletic data performed remotely from computer device  1214 . For example, a user may use a sporting device (described below in relation to BAN  1202 ) and upon returning home or the location of equipment  1222 , download athletic data into element  1222  or any other device of system  1200 . Any I/O device disclosed herein may be configured to receive activity data. 
     2. Body Area Network 
     BAN  1202  may include two or more devices configured to receive, transmit, or otherwise facilitate the collection of athletic data (including passive devices). Exemplary devices may include one or more data acquisition units, sensors, or devices known in the art or disclosed herein, including but not limited to I/O devices  116 - 122 . Two or more components of BAN  102  may communicate directly, yet in other embodiments, communication may be conducted via a third device, which may be part of BAN  102 , LAN  104 , and/or WAN  106 . One or more components of LAN  104  or WAN  106  may form part of BAN  102 . In certain implementations, whether a device, such as portable device  112 , is part of BAN  102 , LAN  104 , and/or WAN  106 , may depend on the athlete&#39;s proximity to an access point to permit communication with mobile cellular network architecture  108  and/or WAN architecture  110 . User activity and/or preference may also influence whether one or more components are utilized as part of BAN  102 . Example embodiments are provided below. 
     User  124  may be associated with (e.g., possess, carry, wear, and/or interact with) any number of devices, such as portable device  112 , shoe-mounted device  126 , wrist-worn device  128  and/or a sensing location, such as sensing location  130 , which may comprise a physical device or a location that is used to collect information. One or more devices  112 ,  126 ,  128 , and/or  130  may not be specially designed for fitness or athletic purposes. Indeed, aspects of this disclosure relate to utilizing data from a plurality of devices, some of which are not fitness devices, to collect, detect, and/or measure athletic data. In certain embodiments, one or more devices of BAN  102  (or any other network) may comprise a fitness or sporting device that is specifically designed for a particular sporting use. As used herein, the term “sporting device” includes any physical object that may be used or implicated during a specific sport or fitness activity. Exemplary sporting devices may include, but are not limited to: golf balls, basketballs, baseballs, soccer balls, footballs, powerballs, hockey pucks, weights, bats, clubs, sticks, paddles, mats, and combinations thereof. In further embodiments, exemplary fitness devices may include objects within a sporting environment where a specific sport occurs, including the environment itself, such as a goal net, hoop, backboard, portions of a field, such as a midline, outer boundary marker, base, and combinations thereof. 
     In this regard, those skilled in the art will appreciate that one or more sporting devices may also be part of (or form) a structure and vice-versa, a structure may comprise one or more sporting devices or be configured to interact with a sporting device. For example, a first structure may comprise a basketball hoop and a backboard, which may be removable and replaced with a goal post. In this regard, one or more sporting devices may comprise one or more sensors, such as one or more of the sensors discussed above in relation to  FIGS.  1 - 3   , that may provide information utilized, either independently or in conjunction with other sensors, such as one or more sensors associated with one or more structures. For example, a backboard may comprise a first sensor configured to measure a force and a direction of the force by a basketball upon the backboard and the hoop may comprise a second sensor to detect a force. Similarly, a golf club may comprise a first sensor configured to detect grip attributes on the shaft and a second sensor configured to measure impact with a golf ball. 
     Looking to the illustrative portable device  1212 , it may be a multi-purpose electronic device, as discussed above in reference to portable device  138  of  FIG.  1   . The portable device  1212  may include a telephone and/or a digital music player, as discussed above. As known in the art, digital media players can serve as an output device, input device, and/or storage device for a computer. Device  1212  may be configured as an input device for receiving raw or processed data collected from one or more devices in BAN  1202 , LAN  1204 , or WAN  1206 . In one or more embodiments, portable device  1212  may comprise one or more components of computer device  1214 . For example, portable device  1212  may be include a display  1216 , image-capturing device  1218 , and/or one or more data acquisition devices, such as any of the I/O devices  1216 - 1222  discussed above, with or without additional components, so as to comprise a mobile terminal. 
     B. Managing Energy Expenditure Estimates from Multiple User Devices 
     In some cases, as shown in  FIGS.  13 A-B , the user  124  may own and/or use multiple athletic activity monitoring devices to monitor one or more metrics, such as energy expenditure, heart rate, pace, distance, among others, during athletic activity performed over a specified duration. (e.g., an hour, a day, a week, a month, etc.), such as duration t 0 -t 20 . For example, the user  124  may own and/or use one or more wrist-worn devices  142 ,  1228 , one or more shoe-mounted devices  140 ,  1226 , one or more computer devices (e.g., portable device  138 ,  1212 , computer device  102 ,  1214 , server  134 ,  1211 , etc.) and/or one or more sporting devices, such as equipment  1222 . Over time, the user  124  may desire to use one or more of these devices individually, or in combination. For example, the user may perform an exercise (e.g., running, basketball, etc.) using the wrist-worn device  142 ,  1228  and the shoe-mounted device  140 ,  1226 . In another illustrative example, the user  124  may additionally use the one or more computing devices to further monitor any athletic activities performed, in combination with the wrist-worn device  142 ,  1228  and/or the shoe-mounted device  140 ,  1226 . 
     Sometimes, the user  124  may desire to use one or more of the above-mentioned or other athletic activity monitoring devices individually. Other times, the user  124  may use the athletic activity monitoring devices in some combination. For example, the user  124  may make the decision about which of the one or more athletic activity monitoring devices to use based upon an exercise type and/or an activity to be performed. In an illustrative example, the user  124  may use a first wrist-worn device  124 ,  128  when performing a first activity (e.g., walking, tennis, swimming, etc.) and a second wrist-worn device  124 ,  1228  for a second activity (e.g., running, biking, etc.). The user  124  may base the decision of which device to use based on one or more factors, including, but not limited to, a feature set associated with either the first or second wrist-worn devices  142 ,  1228 . For example, the second wrist-worn device  142 ,  1228  may include features not available to and/or implemented in the first wrist-worn device  142 ,  1228 , such as an interface to a global positioning system and/or a health monitoring device (e.g., a heart rate monitor, an oxygen sensor, etc.). 
     In an illustrative embodiment, one or more of the athletic activity monitoring devices (e.g., wrist-worn device  142 ,  1228 , shoe-mounted device  140 ,  1226 , portable device  138 ,  1212 , computer device  102 ,  1214 , server  134 ,  1211 , equipment  1222 , etc.), may include at least one processor, a sensor, a communication circuit, a display and/or other circuits for monitoring and/or communicating information about exercises performed by the user  124 . In some cases, the communication circuit may be configured to communicate at least energy expenditure information over a network, such as the BAN  1202 , the LAN  1204  and/or the WAN  1206 . For example, the communication circuit may be configured to communicate, via a wired and/or a wireless link, between the apparatus and at least a second device. In some cases, the energy expenditure information may include at least a first energy expenditure estimate corresponding to a first exercise monitored by the first sensor during a first time frame and a second energy expenditure estimate corresponding to a second exercise monitored by one or more different devices during a second time frame. 
     One or more of the athletic activity monitoring devices may be configured to obtain motion data from movements performed by the user  124  and determine an energy expenditure estimate of the user  124  corresponding to the monitored first exercise, as discussed above. In some cases, a device, such as equipment  1222 , may communicate activity information about the user to a different device (e.g., the computer  1214 , the portable device  1212 , the wrist-worn device  1228 , and/or the shoe-mounted device  1226 ), such that a different device than the device collecting the motion computes at least a portion of the energy expenditure estimate based on the information received from the equipment  1222 . After the energy expenditure estimate is determined, some and/or all energy expenditure estimate determined by the one or more different athletic activity monitoring devices may be communicated over one or more of the BAN  1202 , the LAN  1204 , and the WAN  1206 . For example, the system  1200  may be configured to synchronize different energy expenditure estimates (e.g., a first energy expenditure estimate determined by the wrist-worn device  1228 , a second energy expenditure estimate determined by the shoe-mounted device  1226 , a third energy expenditure estimate determined by the computer device  1228 , etc.) between the two or more different devices associated with a particular user  1284 . 
       FIG.  13    shows a chart illustrating the collection of motion data from two or more sensors over a duration of time (t). Specifically,  FIG.  13 A  shows chart  1300  that illustrates the collection and/or synchronization of motion data in relation to activities performed by the user  124  and  FIG.  13 B  shows chart  1350  that illustrates the collection and/or a more regularly scheduled synchronization of motion data in relation to a specified time interval. In some cases, such as during various time intervals between t 1  and t 7 , two or more devices  1310 - 1340  may be used to monitor a same exercise. In some cases, one or more or the devices  1310 - 1340  may include sensors and/or algorithms that may be configured to provide more accurate and/or detailed metrics corresponding to a particular activity performed by the user  124 . For example, the user  124  may use a general-purpose energy tracker (e.g., a first device  1310 ) to generally monitor activities performed during the day. In some cases, however, the user  124  may desire a more accurate and/or detailed metrics when performing a particular exercise, such as during athletic training. Here, the user  124  may remove the first device  1310  (e.g., a wrist-worn general purpose energy tracking device) and use a second device  1310  having features configured for monitoring a particular athletic activity. In some cases, the user  124  may desire to use two or more of the devices  1310 - 1340  when monitoring a particular athletic activity. In such cases, one or more of the devices may be configured to provide more detailed metrics about at least a portion of the athletic activity to be performed by the user  124 . For example, a shoe-mounted device  140 ,  1226  may be configured to provide information (e.g., force metrics) that may be combined with acceleration and/or distance metrics provided by sensors in a wrist-worn device  142 ,  1228 . The devices  1310 - 1340  may be configured to synchronize obtained over a time period and to combine the synchronized metrics to provide a more accurate and/or detailed assessment of the athletic activities performed by the user  124 . 
     In one embodiment, at least two sensors configured to collect motion data may be located on separate devices. As mentioned above, the user  124  may desire to use different combinations of the one or more devices over a particular duration (e.g., a day). Each individual device may be configured to determine an energy expenditure estimate corresponding to an amount of energy expended by the user  124  while using that particular device. However, the user  124  may desire to view the user&#39;s total energy expenditure estimate for all exercises and/or athletic activities performed, for example, over a course of a day, on each of the different devices. This may be especially advantageous when one or more sensors are stationary and/or difficult to possess or otherwise use throughout the day. For example, a camera-based sensor may be associated with a console or stationary computing device, and as such, may not be utilized to track the user&#39;s  124  all-day activity. Likewise, certain all-day activity trackers may accurately detect or measure most activities, however, are not as accurate as other sensors and/or devices for specific motions and/or activities that user  124  engages in. Sometimes, different devices may be configured to synchronize, such as via the BAN, LAN, and/or WAN to a computing device (e.g., server  1211 ). In some cases, the server  1211  may be configured to determine the total energy expenditure estimate for the user  124  when each device has synchronized energy expenditure information with the server  1211 . To view this total energy expenditure estimate, the user  124  may log into the server  1211  using one or more devices, such as the portable device  1212  and/or the computing device  1214 . However, in some cases, logging into the server  1211  over the WAN may be inconvenient for the user. For these times, and others, it may be desired for at least some of the athletic activity monitoring devices to compute and/or display the total energy expenditure information of the user for a particular time period. 
     In some cases, two or more of the computer  1214 , the portable device  1212 , the wrist-worn device  1228 , and/or the shoe-mounted device  1226  and the exercise equipment  1222  may be configured to exchange, or otherwise communicate, information about exercises performed by the user  124 . In some cases, the information may include, but not be limited to, energy expenditure estimates, activity start times and/or end times, device usage start times and/or end times, system clock information, sensor information (e.g., a force, a velocity, an acceleration, gyroscopic information, etc.), and/or an activity type. The athletic activity monitoring devices may be configured to automatically synchronize (e.g., communicate) the information, such as at the expiration of a specified time interval (e.g., 10 minutes, 15 minutes, 1 hour, etc.), at a start and/or end time associated with use of a device, and/or at a start and/or end time associated with a particular exercise. In other cases, the user  124  may trigger, or otherwise begin, a synchronization process, such as by using an input of one or more of the devices. 
     The charts  1300  and  1350  show illustrative use of multiple sensors, wherein at least two sensors are associated with different devices, over a particular duration, t 0 -t 20  (e.g., 24 hours). In these illustrative examples, the user  124  may use multiple devices  1310 - 1340 , such as over a course of a time duration, e.g., a day. For example, the devices may include a first wrist-worn device  1310 , a second wrist-worn device  1320 , a shoe-mounted device  1330  and a computer device  1340 . In some cases, the user  124  may use two or more devices serially, such as the first wrist-worn device  1310 , such as between times t 1  and t 4 , and t 6  and t 20  and the second wrist-worn device  1320 , such as between times t 4 , and t 6 . For example, the user may wear the first wrist-worn device  1310  for monitoring one or more activities over the course of a day. In some cases, however, the user  124  may desire to use the second wrist-worn device  1320 . For example, the user  124  may desire to wear a GPS enabled device during a run and/or bicycle ride or a water-proof device during a swim, to name two examples. In other cases, two or more of the devices  1310 - 1340  may be used simultaneously. For example, the shoe-worn device  1330  and/or the computer device  1340  may be used in parallel with one or more of the other devices  1320 - 1340 . For example, the shoe-worn device  1330  may be used simultaneously with the first wrist-worn device  1310  from t 2 -t 3 , the second wrist-worn device from t 4 -t 5 , and the computer device from t 3 -t 5 . Similarly, the computer device  1340  may be used with the first wrist worn device  1310  from t 3 -t 4  and t 6 -t 7  and with the shoe-worn device  1330  from t 3 -t 5 . 
     During use, each of the different devices  1310 - 1340  may be configured to communicate, by a communication circuit and one or more communication networks  1202 - 1206 , energy expenditure information between the different devices  1310 - 1340 . For example, the energy expenditure information communicated by the devices  1310 - 1340  may include at least a first energy expenditure estimate determined from a sensor located on a first device and a second energy expenditure estimate determined from a sensor on a second device. The sensor data may be processed on the device comprising the sensor collecting the data and/or a remote device. As mentioned above, in some cases, the devices  1310 - 1340  may be configured to communicate energy expenditure information at specified times. For example, the devices  1310 - 1340  may be configured to synchronize energy expenditure information at a start of a monitored duration (e.g., time t 0 ) and/or at an end of a monitored duration (e.g., time t 20 ). In some cases, the devices  1310 - 130  may be configured to synchronize energy expenditure information at the start time (e.g., t 1 , t 2 , t 3 , t 4 , t 6 ) and/or the end time (e.g., t 4 , t 5 , t 6 , t 7 ) associated with use of the devices  1310 - 1340 . In some cases, the synchronization times may correspond to one or more exercises performed during use of the devices  1310 - 1340 , which may or may not correspond to the usage time of the devices  1310 - 1340 . For example, a particular exercise may be monitored by use of two or more of the devices  1310 - 1340 , where the exercise may continue after one of the devices is no longer used. In other cases, an indication that the exercise has ended may be determined from the motion data showing that the user  124  is no longer actively using one or more of the devices  1310 - 1340 . In some cases, as shown in chart  1350 , one or more devices (e.g., devices  1310 - 1340 ) may be configured to synchronize, or otherwise communicate, energy expenditure information after a specified time interval Δt has elapsed (e.g., at regular time intervals during the duration t 0 -t 20 ). In some cases, one or more of devices  1310 - 1340  may include a system clock that may be used at least for associating time information to monitored and determined energy expenditure information. The system time kept by the system clock may be used during normal operation of the devices  1310 - 1340  and/or during synchronization. In some cases, one or more of the devices  1310 - 1340  may be configured to synchronize or otherwise set each clock to a similar time as part of the synchronization process and/or to facilitate the synchronization process. 
       FIGS.  14 A-B  show illustrative block diagram representations of at least a portion of a device  1400 ,  1450 , respectively for determining and/or outputting energy expenditure estimates. As discussed above, the devices  1400 ,  1450  may include a display  1440  configured for displaying one or more energy expenditure values to a user  124 . Also, the device  1400 ,  1450  may be configured to determine an energy expenditure estimate for motions performed by a user. In certain embodiments, the same device comprises the sensor utilized to capture the motion data. During a specified time period, such as over a day (e.g., t 0 -t 20 ), the user  124  may use two or more different devices  1310 - 1340 , such as to obtain the device-specific data sets over time, where each of the different devices determine an individual energy expenditure estimate  1410 . In some cases, the user  124  may desire to view and/or review a total energy expenditure estimate, such as over a day. 
     In an illustrative synchronization example referring to  FIG.  13   , the user  124  may begin a day (e.g., duration t 0 -t 20 ) by using a first device  1310  comprising at least one sensor configured to detect movements of the user. Upon use, the first device  1310  may communicate, or otherwise synchronize any accumulated data, such as for example, energy expenditure estimates determined by, for example, the second device  1320 . The first device  1310  may then monitor activities performed by the user  124  over a first time a period (e.g., t 1 -t 4 ) and determine a first energy expenditure estimate corresponding to the monitored activities. After computing the first energy expenditure estimate, the first device  1310 , either manually or automatically, may synchronize the first energy expenditure estimate with at least the second device  1320 . For example, a manual synchronization may be performed in response to a request (e.g., an input) received from the user  124 . An automatic synchronization may be performed in response to one or more conditions determined by the apparatus  1310 - 1320  and/or communicated to the apparatus  1310 - 1320 , such as an expiration of a repeating timer, a determined activity state, a determined time period, and/or one or more other conditions. 
     At a second time period (e.g., t 4 -t 6 ), the user  124  may use the second device  1320  to monitor activities and determine a corresponding second energy expenditure estimate. After computing the second energy expenditure estimate, the second device  1320  may synchronize the second energy expenditure estimate with the first device  1310 . Upon synchronization, the first device and/or the second device may be configured to determine and/or output a total energy expenditure estimate corresponding to the first energy expenditure estimate and the second energy expenditure estimate. In some cases, one or more of the first device and the second device may be configured to synchronize the determined total energy expenditure estimate. If differences are found between the synchronized values (e.g., due to accuracy differences, algorithm differences, etc.), one of the first device or the second device may be configured to modify or adjust the total energy expenditure estimate and to synchronize the modified total energy expenditure estimate between the devices  1310 ,  1320 . 
     In some cases, two or more sensors of two or more devices  1310 - 1340  may obtain data from the user during the same absolute time period. In such cases, each device  1310 - 1340  may be configured to synchronize individual energy expenditure estimates determined by each device. In some cases, one or more of the devices may be configured to determine a combined energy expenditure estimate during the common time period based, at least in part, on the energy expenditure estimates of each synchronized device during the common time period, similarly to the illustrative example of  FIG.  8   , as discussed above. The combined energy expenditure estimate may be based on the accuracy in calculating energy expenditure for all of the available sensors or sensor systems. For example, metrics obtained using a first sensor of the first device  1310  may be combined with second metrics obtained from one or more of the devices  1320 - 1340  during a common time period (e.g., t 2 -t 4 ). The metrics from the devices  1310 - 1340  may be combined using one or more algorithms based, at least in part, on a type of sensor used to collect the metrics, an accuracy of the sensor, an activity performed by the user  124 , and the like. The selection of a particular sensor and/or device  1310 - 1320  and/or the accuracy of the sensors may be functions of the exercise that will be performed. For example, a first sensor may result in more accurate energy expenditure calculations while a user is running and a second sensor may result in more accurate energy expenditure calculations while a user is performing squats. In such cases, the combined energy expenditure estimate may be calculated using one or more of an average, a weighted average or a statistical solution to determine energy expenditure. 
     In some cases, such as during time period t 13 -t 14 , two or more of the devices  1310 - 1340  may be used to determine one or more metrics about athletic activity performed by the user  124 . In some cases, the user  124  may determine which ones of the two or more devices  1310 - 1340  to use when monitoring any athletic activity, such as by specifying a device having the greatest accuracy for a particular metric. In other cases, the two or more devices  1310 - 1340  may be configured to determine, such as via a network (e.g., the BAN  1202 , the LAN  1204 , the WAN  1206 ) which of the devices  1310 - 1340  may have a greater accuracy associated with a metric associated with an athletic activity performed by the user. For example, the device  1310  may receive an indication from at least one other device (e.g., device  1330 ,  1340 ) that the at least one other device  1330 ,  1340  is being used to monitor athletic activity of the user  124 . In some cases, the first device  1310  may broadcast an indication via the networks  1202 - 1206  that the first device  1310  is monitoring the athletic activity of the user  124 . Next, the different devices  1310 - 1340  being used to monitor the same athletic activity of the user  124  may be configured to determine which one(s) of the devices  1310 - 1340  may be used to determine a metric (e.g., energy expenditure, blood pressure, force, heart rate, acceleration, velocity, etc.) associated with the athletic activity of the user  124 . For example, a first device may be determined as having the greatest accuracy for a particular desired metric may be used to monitor that metric. In such cases, information about the metric may be synchronized with and/or used by the other devices  1320 - 1340 , such as to determine an energy expenditure estimate of the user  124 . In some cases, the metric may be synchronized between the different devices  1310 - 1340  at predetermined intervals (e.g., 4 seconds, 10 seconds, 30 seconds, etc.). In other cases, each of the devices  1310 - 1340  may each determine the particular metric, where the metric may be combined to determine a common metric over the monitored duration. 
     After determining the total energy expenditure estimate one or more devices, e.g. devices  1310 - 1340 , may be configured to synchronize the total energy expenditure estimate over one or more of the BAN  1202 , the LAN  1204  and/or the WAN  1206 . In some cases, a device, such as the first device  1310  may be configured to be a master of the system and the other devices  1320 - 1340  may be configured as slaves. For example, the first device  1310  may receive the energy expenditure estimates from one or more other devices  1320 - 1340  to determine the total energy expenditure estimate and then synchronize the total energy expenditure estimate with the other devices  1320 - 1340  on the network. 
     When computing the total energy expenditure estimates, the devices  1310 - 1340  may be configured to display and/or manage the energy expenditure information using two or more different methods. For example, a device  1400  may be configured to determine a total energy estimate from two or more different energy expenditure estimates synchronized over a network (e.g., BAN  1202 , LAN  1204 , WAN  1206 ). For example, the device  1410  may be configured to determine a local energy expenditure estimate  1410 , and to synchronize the local energy expenditure estimate  1410  with one or more different energy expenditure estimates  1415  synchronized over the network via a communication interface  1420 . In some cases, the synchronized energy expenditure estimates  1415  may be combined (e.g., summed) using one or more computation modules  1425  to determine the total energy expenditure estimate  1430 . In some cases, the total energy expenditure estimate  1430  may be computed by the computation module  1425  using one or more algorithms, weighting factors, or the like. 
     Once computed, the total energy expenditure estimate  1430  may be used as a baseline energy expenditure estimate. In one embodiment, the baseline energy expenditure estimate may then be used to overwrite the local energy expenditure estimate  1410 , such that any further energy expenditure estimate determined by the device  1450  is added to the new baseline value. The new baseline value may then be synchronized between the different devices on the network via the communication interface  1420 . In some cases, the device  1410  may include a display  1440  that may be utilized to display one or more of the local energy expenditure estimate  1410 , the synchronized energy expenditure estimate  1414  and/or the total energy expenditure estimate  1430 . In some cases, the display may be configured to display an indication of a synchronization status of the network. 
     In some cases, the apparatus  1450  may be configured to determine the local energy expenditure estimate  1460 . The communication interface  1420  may be configured to synchronize two or more energy expenditure estimates between the device  1450  and one or more different devices. For example, the energy expenditure estimates may be stored in different memory areas, such as in the system memory  108 , of the device  1450 . A first energy expenditure estimate  1462  received from a first device may be stored in a first memory area, a second energy expenditure estimate  1464  received from a second device  1330  may be stored in a second memory area, and so on. In some cases, the different energy expenditure estimates  1460 - 1464  stored in the system memory  108  may be used to determine the total energy expenditure estimate. For example, the device  1450  may use the different energy expenditure estimates as an offset which may be added to the local energy expenditure estimate  1460 . In some cases, the two or more of the different energy expenditure estimates  1460 - 1464  may be combined to determine a time interval common to the first energy expenditure estimate and the second energy expenditure estimates  1464  and combine the energy expenditure estimates associated with the common time period to determine a third energy expenditure estimate corresponding to an exercise performed by the user  124 . In some cases, the device  1450  may be configured to determine a total energy estimate by combining (e.g., summing, applying weighting factors, applying an algorithm, etc.) using the computation module  1425 . The computation module may store the total energy expenditure estimate  1480 . In some cases, the display  1440  may be configured to present, to the user  124 , one or more of the local energy expenditure estimate  1460 , the energy expenditure estimates of the two or more different devices  1462 - 1464  and/or the total energy expenditure estimate  1480 . 
       FIG.  15    illustrates an example flow diagram  1500  of a method for calculating a combined energy expenditure estimate for a user  124  based on energy expenditure estimates obtained by two or more different devices  1310 - 1340 . The method may be implemented by a computer, such as, for example, computer  102 , device  138 ,  140  and/or  142 , as well as or other apparatuses  1211 - 1214 ,  1222 - 1228 , and/or  1310 - 1340 . The blocks shown in  FIG.  15    may be rearranged, some blocks may be removed, additional blocks may be added, each block may be repeated one or more times, and the flow diagram may be repeated one or more times. At  1502 , the processor  106  of a first device  1310  may be configured to determine first energy expenditure information associated with a first athletic activity performed by the user  124 . In some cases, the first energy expenditure information may include a first energy expenditure estimate and one or more different time stamps, such as first time stamp associated with a start of a first athletic activity and/or a second time stamp associated with an end of the first athletic activity. In some cases, the second device  1320  may determine the second energy expenditure information associated with a second athletic activity of the user. The second energy expenditure information may include a second energy expenditure estimate and at least one second time stamp associated with the second athletic activity. At  1504 , the first device  1310  may synchronize the first energy expenditure information with second energy expenditure information of a second device (e.g., one or more of the devices  1320 - 1340 ), such as over a network (e.g., the BAN  1202 , the LAN  1204 , and/or the WAN  1206 ). 
     At  1506 , the first device  1310  may determine, such as by using the processor  108 , a total energy expenditure estimate based, at least in part, on the first energy expenditure information and the second energy expenditure information. At  1508 , the first device may display at least the total energy expenditure estimate, such as to the user  124 . In some cases, the first device  1310  and/or the second device  1320  may determine a different energy expenditure estimate used by the first device  1310 , such as by overwriting at least one of the first energy expenditure estimate and the second energy expenditure estimate with the total energy expenditure estimate. In some cases, the first device may determine the total energy expenditure estimate as a combination of a first offset associated with the first energy expenditure estimate and a second offset associated with the second energy expenditure estimate. The display may display the total energy expenditure estimate as a combination of at least the first offset and/or the second offset. In some cases, the display may display energy expenditure information for the first device  1310  and/or one or more of the different devices  1320 - 1340  after synchronizing the energy expenditure information. 
       FIG.  16    shows an illustrative chart showing use of two devices capable of monitoring energy expenditure of a user while performing one or more athletic activities and/or exercises over a common time interval. For example, a user may perform one or more athletic activities (e.g., running, biking, daily activities, etc.) over a time interval. As discussed herein, multiple sensors or devices may monitor or otherwise sense (actively or passively) the user&#39;s activities. As such, parameters relating to the user&#39;s activity may be captured using sensors, which may be located on one or more devices. The sensors may monitor the user&#39;s motion, physiological properties, and/or other parameters. As discussed above, a first sensor may result in more accurate determinations, such as for example, energy expenditure calculations while a user is running and a second sensor may result in more accurate determinations, e.g., energy expenditure calculations, while a user is performing squats. Although the following examples (as well as other examples disclosed herein) provide examples with reference to energy expenditure, these are merely examples and not intended to limit the scope of this disclosure. In instances where data regarding certain parameters, such as energy expenditure, are obtained from two or more sensors or determined by different mathematical calculations, certain aspects of this disclosure may be implemented to determine a resultant output. In such cases, the combined energy expenditure estimate may be calculated using one or more of an average, a weighted average or a statistical solution. However, such calculations may not be practical in every situation. As such, another method of combining energy expenditure information gathered using different devices may be desired. 
     For example, in some cases, a user may perform athletic activities using sensors provided by two or more vendors. As such, a simple set of easily understandable rules for combining energy expenditure information may be desirable. Such rules may be applied in a common manner across all users and/or for devices provided by multiple vendors. The rules may include ensuring that a user&#39;s recorded total energy expenditures will never decrease and that information gathered during one or more sessions of athletic activity will be preserved. In such cases, the energy expenditure information may always be available and/or accessible to a user via an application, whether or not the energy expenditure information is directly reflected in the total energy expenditure information. 
     In certain implementations, a device, such as the device  1400 ,  1450  may determine whether energy expenditure information received from at least two devices overlap over one or more time intervals. Certain embodiments may determine whether a minimum threshold of an interval is met. For example, if a second device or sensor only intermittently provides data, it may not meet a threshold requirement for further analysis. Intervals may be any time unit, including fractions of a second, seconds, minutes, hours, days, etc. and derivatives thereof. If two or more sensors or device gather information or for a threshold amount of information, If so, energy expenditure information from the device which recorded the most energy expenditures over a particular time interval may be used. The determination of “most” or highest may be unit dependent, such as highest peak value during any unit of time within the time interval, the highest cumulative values, the highest average value over the overlapping collection period, among others. The determination of which parameters or values to use may be made by device  1400 ,  1450 . 
     Unlike other methods discussed herein, the energy expenditure information may not be combined. Rather, the device  1400 ,  1450  may determine one or more time intervals during which energy expenditure information overlap for two or more sensors/devices recording the user&#39;s athletic activities, as shown in  FIG.  16   . Here, energy expenditure information may be received over a first time period  1655 . During this time a user may perform one or more athletic activities and use one or more sensors for monitoring the activity. The chart  1600  shows an illustrative example of a user participating in an athletic activity over the time period  1655 . Here, the user may use a first sensor  1610  (e.g., a wrist worn sensor) to provide a first energy expenditure estimate  1612  over the time period  1655  and a second sensor  1620  (e.g., a camera) to provide a different second energy expenditure estimate  1622  over at least a portion of the same time period  1655 . Or perhaps, the user has a mobile device, e.g., mobile telephone or tablet in their pocket or being carried that measures movements. Thus, while the mobile device in the pocket or bag may be less accurate in some embodiments due to capturing less motion, it will serve as a fall back device for when the more accurate device is not available, such as by the battery dying or the user removing it from their wrist. The device  1400 ,  1450  may be configured to receive the first and second energy expenditure estimates  1612 ,  1622  from the first device  1610  and the second device  1620  and to combine this energy expenditure information into a total energy expenditure estimation  1630  over the time period  1655 , as shown in the chart at  1632 . 
     To generate the total energy expenditure estimation  1630 , the device  1450 ,  1455  may receive, such as via a synchronization process, the energy expenditure information from the first sensor  1610  and the second sensor  1620  via a communication link (e.g., a wireless communication link, a wired communication link, and/or combinations thereof). The first energy expenditure estimate  1612  and the second energy expenditure estimate  1622  may be analyzed over the time period  1655  to determine one or more sub-time periods  1665 ,  1675 ,  1685 , where the energy expenditure estimates  1612 ,  1622  provided by first sensor  1610  and the second sensor  1620  overlap (which may be subjected to threshold requirements). During this analysis, the device  1400 ,  1450  may determine each sub-time period  1665 ,  1675 ,  1685  based on which of the sensors  1610 ,  1620  has provided the greater or larger amount of energy expenditure information  1612 ,  1622  during that particular time period. For example, over the first sub-time period  1665  and the third sub-time period  1685 , the first sensor  1610  has provided the most energy expenditure information over those time intervals and during the second sub-time interval  1675 , the second sensor  1620  has provided the greater amount of energy expenditure information. In this case, the determination is based upon the largest accumulation of energy expenditure units during the overlapping period, however, as discussed above, other determinations are within the scope of this disclosure. In some cases, two or more sensors may be used over the complete time interval  1655 . In other cases, one or more sensors may be used over a portion of the complete time interval  1655 , as shown in the illustrative example of chart  1600 . Here, the second sensor  1620  may have been used primarily during the second sub-time interval  1665 . 
     To determine the total energy expenditure estimate  1632 , the device  1400 ,  1450  may process the first and second energy expenditure estimates  1612 ,  1622  using an energy expenditure calculation module, which may comprise hardware and software. For example, the device  1400 ,  1450  may determine the total energy expenditure estimate  1632  based on which sensor  1610 ,  1620  provides a greater of energy expenditure estimate over a particular sub-time period  1655 ,  1675 ,  1685 . As can be seen in the chart  1600 , the first sensor provides a greater amount of energy expenditure information over the first and third time intervals  1665 ,  1685 , 100 units of energy expenditure information and 50 units, respectively. Over the second time period  1675 , the second sensor  1620  provides the greater cumulative amount of energy expenditure information (e.g., 300 units vs. 200 units). As such, total energy expenditure estimate  1632  corresponds primarily to the first energy expenditure estimate  1612  over the first and third sub-time intervals  1665 ,  1685 , and to the second energy expenditure estimate  1622  over the second sub-time interval  1675 . This may be advantageous in implementations in which a mobile device is routinely available as a fall back device, however, data from the more specialized device may be used when available. In some cases, the device  1400 ,  1450  may smooth the total energy expenditure estimate  1632  at the transition between time intervals (e.g., between the first sub-time interval  1665  and the second sub-time interval  1675  and between the second sub-time interval  1675  and the third sub-time interval  1685 ). Those skilled in the art will appreciate that the illustrative algorithm used to process the energy expenditure information received from the different sensors over a common time period is illustrative and other such algorithms for combining the energy expenditure information may be used, such as by using an average, using one or more weighting factors, adding a difference, and the like. 
       FIG.  17    shows illustrative chart  1600  (replicated on a smaller scale from  FIG.  16   ) and chart  1700  showing use of three or more devices  1610 ,  1620 ,  1740  capable of monitoring energy expenditure of a user while performing one or more athletic activities and/or exercises over a common time interval  1655 . In the illustrative use case shown in  FIG.  17   , three devices  1610 ,  1620 ,  1730  may be used to monitor athletic activity of the user over the common time interval  1685 . For example, the user may use a wrist-worn sensor, a camera and an acceleration sensor. In some cases, one or more of the sensors  1610 ,  1620 ,  1740  may communicate with a software application that may process raw sensor data to calculate energy expenditure information subsequently provided to the device  1400 ,  1450 . In some cases, the energy expenditure information  1612 ,  1622 , and  1742  may be communicated to the device  1400 ,  1450  for processing via a communication link, such as by asynchronously synchronizing the sensors to the device. In some cases, the sensor information may be synchronously communicated to the device  1400 ,  1450 . 
     Once the energy expenditure estimates  1612 ,  1622 ,  1742  have been received, the device  1400 ,  1450  may process the energy expenditure estimates  1612 ,  1622 ,  1742 , e.g., using computer-executed instructions stored on a non-transitory computer-readable medium. to generate a total energy expenditure estimate  1752  of the user during the time interval  1655 . In an illustrative example, the device may first process the energy expenditure information received from the first and second devices to produce a total energy expenditure estimate  1632 , as discussed above in reference to  FIG.  16   . Once calculated, the device  1400 ,  1450  may then combine the energy expenditure estimate  1742  with the total energy expenditure estimate  1632  to provide a new total energy expenditure estimate  1752  corresponding to the combined energy expenditure information received from the sensors  1610 ,  1620 , and  1740 . The new energy expenditure information may be determined by comparing the total energy expenditure estimate  1632  with the third energy expenditure estimate  1742  over the different sub-time intervals  1665 ,  1675  and  1685 . As before, for a particular sub-time interval, the new total energy expenditure estimate  1752  may correspond to the energy expenditure estimate  1632 ,  1742  having the greater value over each particular sub-time interval  1665 ,  1677 ,  1685 . As can be seen from the illustrative chart  1700 , the new total energy estimate  1752  corresponds to the previous total energy expenditure  1632  estimate over the first and third time intervals  1665 ,  1685  and with the third energy expenditure estimate  1742  over the second time interval  1675 . In some cases, the new total energy expenditure estimate  1752  may be smoothed at the transition between the first sub-time interval and the second sub-time interval and between the second sub-time interval and the third sub-time interval. 
     In some cases, one or more sensors may synchronize with different devices to compute a total energy expenditure estimate. Each of the different devices may separately compute a total energy expenditure estimate based on the devices synchronized. In some cases, the devices may further synchronize the energy expenditure information. In other cases, each device may individually aggregate energy expenditure information. For example, a user may use sensors from two or more different vendors, where a first set of sensors may be configured to synchronize energy expenditure information with a first device and a second set of sensors may be configured to synchronize energy expenditure information with a second device. In such cases, the energy expenditure information may be totaled separately on the different devices. For example, the first device may store a total energy expenditure estimate of 5000 units gathered using the first set of sensors and the second device may store a total energy expenditure estimate of 6000 units gathered using the second set of sensors. 
     Conclusion 
     Providing an activity environment having one or more of the features described herein may provide a user with an immersive experience that will encourage and motivate the user to engage in athletic activities and improve his or her fitness. Users may further communicate through social communities and challenge one another to reach various levels of fitness, and to view their fitness level and activity. 
     The transmission of information between devices ensures that users are provided with energy expenditure information, regardless of which device they are currently using. Moreover, the energy expenditure information can be collated to provide accurate combined energy expenditure for the user which takes into account the devices used by the user and any overlap in their use. This may enable the user to use devices which are specifically adapted to one or more activities while still retaining an overview of their energy expenditure. Accordingly, devices may be tailored more specifically to certain activities. On the other hand, the system can be setup as a master and slave arrangement which may allow slave devices to have a reduced functionality, which in turn may reduce their complexity, cost, and/or size, without any significant disadvantage for the user. In addition, the communication of information between devices potentially reduces data transmission, processing and storage burdens. 
     Aspects of the embodiments have been described in terms of illustrative embodiments thereof. Numerous other embodiments, modifications and variations within the scope and spirit of the appended claims will occur to persons of ordinary skill in the art from a review of this disclosure. For example, one of ordinary skill in the art will appreciate that the steps illustrated in the illustrative figures may be performed in other than the recited order, and that one or more steps illustrated may be optional in accordance with aspects of the embodiments. 
     In any of the above aspects, the various features may be implemented in hardware, or as software modules running on one or more processors. Features of one aspect may be applied to any of the other aspects. 
     There may also be provided a computer program or a computer program product for carrying out any of the methods described herein, and a computer readable medium having stored thereon a program for carrying out any of the methods described herein. A computer program may be stored on a computer-readable medium, or it could, for example, be in the form of a signal such as a downloadable data signal provided from an Internet website, or it could be in any other form. 
     For the avoidance of doubt, the present application extends to the subject-matter described in the following numbered paragraphs (referred to as “Para” or “Paras”): 
     Para 1. An apparatus for use with a user performing an exercise comprising:
         at least one processor;   a first sensor configured to monitor a first exercise performed by the user;   a communication circuit configured to communicate at least energy expenditure information between the apparatus and at least a second device, the energy expenditure information including at least a first energy expenditure estimate corresponding to the first exercise monitored by the first sensor and a second energy expenditure estimate corresponding to a second exercise monitored by at least the second device;   at least one tangible memory storing computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to:
           monitor, with the sensor, the first exercise performed by the user;   determine, by the at least one processor, the first energy expenditure estimate of the user corresponding to the monitored first exercise;
               communicate, by the communication circuit, energy expenditure information between the apparatus and at least the second device, the energy expenditure information including the first energy expenditure estimate and the second energy expenditure estimate; and   determine, by the at least one processor, a combined energy expenditure estimate of the user based, at least in part, on the first energy expenditure estimate and the second energy expenditure estimate.   
               
               

     Para 2. The apparatus of Para 1, comprising a display for displaying at least the combined energy expenditure estimate of the user. 
     Para 3. The apparatus of Para 1 or 2, wherein the at least one tangible memory stores further computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to communicate the energy expenditure information between the apparatus and at least the second device after expiration of a specified time interval. 
     Para 4. The apparatus of any preceding Para, wherein the at least one tangible memory stores further computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to communicate the combined energy expenditure estimate between the apparatus and at least the second device. 
     Para 5. The apparatus of any preceding Para, wherein the at least one tangible memory stores further computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to communicate the energy expenditure information between the apparatus and at least the second device in response to a synchronization request from the user. 
     Para 6. The apparatus of any preceding Para, wherein the at least one tangible memory stores further computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to automatically communicate the energy expenditure information between the apparatus and at least the second device after determining a completion of at least one of the first athletic activity and the second athletic activity. 
     Para 7. The apparatus of any preceding Para, wherein the energy expenditure information includes at least one of at least one time stamp associated with the energy expenditure estimate, an activity type, and a system clock time. 
     Para 8. The apparatus of any preceding Para, wherein the at least one tangible memory stores further computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to synchronize a system clock of the apparatus with a system clock of the second device. 
     Para 9. The apparatus of any preceding Para, wherein the at least one tangible memory stores further computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to:
         determine a common time interval associated with both the first athletic activity and the second athletic activity; and   determine a third energy expenditure estimate associated with the combined first athletic activity and the second athletic activity during the common time interval, and   determine the combined energy expenditure estimate based, at least in part, on the third energy expenditure estimate.       

     Para 10. The apparatus of any preceding para, wherein the at least one tangible memory stores further computer-executable instructions that, when executed by the at least one processor, cause the apparatus at least to:
         determine a common time interval associated with the first energy expenditure estimate and the second energy expenditure estimate,   determine, for the common time interval, whether the first energy expenditure estimate is greater than the second energy expenditure estimate, wherein:   when the first energy expenditure estimate is greater than the second energy expenditure estimate, set the combined energy expenditure estimate for the common time interval to the first energy expenditure estimate; and   when the first energy expenditure estimate is not greater than the second energy expenditure estimate, set the combined energy expenditure estimate over the common time interval equal to the second energy expenditure estimate.       

     Para 11. A system comprising:
         a first monitoring device configured to determine a first energy expenditure estimate associated with athletic activity performed by a user over a first duration;   a second device, in communication with the first monitoring device, the second device configured to store at least a second energy expenditure estimate associated with athletic activity performed by the same user over a second duration; and   wherein the first monitoring device includes:   a first processor;   a first tangible memory device storing computer-executable instructions that, when executed by the first processor, cause the first monitoring device at least to:
           send, via the communications network, the first energy expenditure estimate to the second device;   receive, via a communications network, the second energy expenditure estimate from the second device; and   determine, by the processor, a total energy expenditure estimate based, at least in part, on the first energy expenditure estimate and the second energy expenditure estimate; and   
           a display to display the total energy expenditure estimate to the user.       

     Para 12. The system of Para 11, wherein the second device comprises:
         a second processor;   a second tangible memory device storing computer-executable instructions that, when executed by the second processor, cause the second device at least to:
           receive, via a communications network, the first energy expenditure estimate from the first monitoring device;   send, via the communications network, the second energy expenditure estimate to the first monitoring device; and   determine, by the second processor, a total energy expenditure estimate based, at least in part, on the first energy expenditure estimate and the second energy expenditure estimate; and   
           a second display for displaying the total energy expenditure estimate to the user.       

     Para 13. The system of any of Paras 11 or 12, wherein the second device comprises:
         a sensor configured to monitor an athletic activity performed by the user; and   wherein the second tangible memory stores further executable instructions that, when executed by the second processor, cause the second device to at least determine the second energy expenditure estimate based, at least in part, on information obtained by the sensor.       

     Para 14. The system of any of Paras 11 to 13, wherein the first tangible memory stores further computer-executable instructions that, when executed by the first processor, cause the first monitoring device at least to synchronize, via the communications network, the total energy expenditure estimate determined by the first monitoring device with the second device. 
     Para 15. The system of any of Paras 11 to 14, wherein the first tangible memory stores further computer-executable instructions that, when executed by the first processor, cause the first monitoring device at least to determine the total energy expenditure estimate as a sum of at least a portion of the first energy expenditure estimate and at least a portion of the second energy expenditure estimate. 
     Para 16. The system of any of Paras 11 to 15, wherein the first tangible memory stores further computer-executable instructions that, when executed by the first processor, cause the first monitoring device at least to:
         determine an exercise performed by the user during a time period common to the first duration and the second duration,   determine a third energy expenditure estimate corresponding to the exercise performed during the common time period; and   wherein the total energy expenditure estimate further includes the third energy expenditure estimate.       

     Para 17. The system of any of Paras 11 to 16, wherein the first tangible memory stores further computer-executable instructions that, when executed by the first processor, cause the first monitoring device at least to:
         synchronize a first system clock associated with the first monitoring device with a second system clock associated with the second monitoring device, and   adjust one or more time stamps associated with the first energy expenditure estimate based on a difference between the first system clock and the second system clock.       

     Para 18. The system of any of Paras 10 to 17, wherein the first tangible memory stores further computer-executable instructions that, when executed by the first processor, cause the first monitoring device at least to overwrite the first energy expenditure estimate with total energy expenditure estimate. 
     Para 19. The system of any of Paras 11 to 18, wherein the first tangible memory stores further computer-executable instructions that, when executed by the first processor, cause the first monitoring device at least to:
         determine an offset corresponding to at least a portion of the second energy expenditure estimate; and   display the total energy expenditure estimate as a sum of the first energy expenditure estimate and the offset.       

     Para 20. A method comprising:
         determining, by a first processor of a first device, first energy expenditure information associated with a first athletic activity of the user, the first energy expenditure information including a first energy expenditure estimate and a first time stamp associated with the first athletic activity;   synchronizing, via a network, the first energy expenditure information with second energy expenditure information of a second device;   determining, by the processor of the first device, a total energy expenditure estimate based, at least in part, on the first energy expenditure information and the second energy expenditure information; and   displaying, on a display device, the total energy expenditure estimate.       

     Para 21. The method of Para 20, further comprising:
         overwriting at least one of the first energy expenditure estimate and the second energy expenditure estimate with the total energy expenditure estimate.       

     Para 22. The method of Para 20 or 21, further comprising determining, by the first processor, the total energy expenditure estimate as a combination of a first offset associated with the first energy expenditure estimate and a second offset associated with the second energy expenditure estimate; and
         displaying, on the display device, the total energy expenditure estimate and at least one of the first offset and the second offset.       

     Para 23. The method of any of Paras 20 to 22 further comprising determining, by a second processor of the second device, second energy expenditure information associated with a second athletic activity of the user, the second energy expenditure information including a second energy expenditure estimate and a second time stamp associated with the second athletic activity. 
     Para 24. A non-transitory computer-readable medium comprising executable instructions that when executed cause a computer device to perform the method as described in any of Paras 20 to 23. 
     Para 25. The method of any of Paras 20 to 24 further comprising:
         determining a common time interval associated with the first energy expenditure estimate and the second energy expenditure estimate,   determining, for the common time interval, whether the first energy expenditure estimate is greater than the second energy expenditure estimate, wherein:   when the first energy expenditure estimate is greater than the second energy expenditure estimate, setting the combined energy expenditure estimate for the common time interval to the first energy expenditure estimate; and   when the first energy expenditure estimate is not greater than the second energy expenditure estimate, setting the combined energy expenditure estimate over the common time interval equal to the second energy expenditure estimate.