Patent Publication Number: US-2021193314-A1

Title: Medical device data analysis

Description:
PRIORITY INFORMATION 
     This application claims priority of U.S. Provisional Application Ser. No. 62/951,963, filed on Dec. 20, 2019, the contents of which are incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates generally to semiconductor memory and methods, and more particularly, to apparatuses, systems, and methods for medical device data analysis. 
     BACKGROUND 
     Medical devices (e.g., implantable medical devices, medical prothesis, etc.) can communicate with scanners, servers, wireless devices, etc. to obtain and exchange information. The medical apparatuses can be implanted into a patient in order to affect biological and/or additional functioning of the patient. Over time, a patient&#39;s needs or the effect of the medical apparatus on the patient can change. In order to avoid adverse effects of the medical device on the patient, for example, the medical device can be checked in order to improve operational efficiency, more closely match with a patient&#39;s needs or recommendations of a physician by communication with an external device. 
     Memory devices can be coupled to other devices (e.g., a computing device, a mobile device, etc.) to store (e.g., write) data, commands, and/or instructions for use by the device while the computer or electronic system of the device is operating. For example, data, commands, and/or instructions can be transferred between the device and the memory device(s) during operation of a computing or other electronic system. 
     Memory devices are typically provided as internal, semiconductor, integrated circuits in computers or other electronic systems. There are many different types of memory including volatile and non-volatile memory. Volatile memory can require power to maintain its data (e.g., host data, error data, etc.) and includes random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), synchronous dynamic random access memory (SDRAM), and thyristor random access memory (TRAM), among others. Non-volatile memory can provide persistent data by retaining stored data when not powered and can include NAND flash memory, NOR flash memory, and resistance variable memory such as phase change random access memory (PCRAM), resistive random access memory (RRAM), and magnetoresistive random access memory (MRAM), such as spin torque transfer random access memory (STT RAM), among others. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a functional block diagram in the form of a computing system including an apparatus in the form of a mobile device in accordance with a number of embodiments of the present disclosure. 
         FIG. 2  is a functional block diagram in the form of a computing system including a mobile device and a plurality of memory devices in accordance with a number of embodiments of the present disclosure. 
         FIG. 3  is a diagram representing an example display of a mobile device for medical device data analysis in accordance with a number of embodiments of the present disclosure. 
         FIG. 4  is a flow diagram representing an example of medical device data analysis in accordance with a number of embodiments of the present disclosure. 
         FIG. 5  is a flow diagram representing an example method for medical device data analysis in accordance with a number of embodiments of the present disclosure. 
         FIG. 6  is a flow diagram representing an example method for medical device data analysis in accordance with a number of embodiments of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     Systems, apparatuses, and methods related to medical device data analysis are described. Medical devices can generate data about a user of the medical device and/or the medical device itself. In some examples, the medical device is implanted in a user of the medical device and the data generated by the medical device is not easily accessible to the user. Medical devices can be coupled to computing systems including memory devices to provide information about the medical device to the user of the medical device. One or more memory devices of the computing system can store information about the medical device and/or the user of the medical device such that the information is accessible to the user. In an example, a controller can be configured to receive, by a mobile device coupled to a medical device, data from the medical device, where the data is a part of a baseline dataset related to the medical device. The controller can be configured to receive different data from the medical device, where the different data is received from the medical device as the different data is generated by the medical device, analyze the data from the medical device and the different data generated by the medical device, and perform an action based on the analyzed data and the different data generated by the medical device. 
     As used herein, storing data can include writing data to a memory media included in a memory device. For example, data can be stored to a memory device by writing the data to a memory media of a memory device. In addition, the data can also be retrieved by a computing device (e.g., a mobile device and/or a controller) from its place of storage. Medical devices can generate data about the health of a user, a body part of a user, and/or the medical device. The data generated by the medical device can be difficult for a user of the medical device to view and/or analyze. 
     In some previous approaches, data generated by a medical device (e.g., an implantable medical device) can be viewed by a user of the medical device when accompanied by a doctor and/or while located at a medical facility setting. Medical devices may include limited memory storage capabilities, as such, in some instances, data generated by a medical device is not saved by the medical device unless the data is considered problematic. However, a user of a medical device may wish to understand the impact of the medical device on their body when performing non-problematic activities. For example, a user of an implantable medical device such as a pacemaker may want to view data generated by the pacemaker while exercising or performing other routine activities. Further, in some instances a user may experience an ostensibly minor incident (e.g., a minor fall, etc.) and wish to know if the medical device registered an abnormality (e.g., a problem). Not being able to view the data in real-time can lead to frustration, wasted time, anxiety, and/or wasted resources to travel to a medical facility to be informed that the medical device did not store any information about the ostensibly minor incident. 
     In contrast, as will be described herein, communicatively coupling a medical device to a computing system (e.g., a mobile device) corresponding to a user of the medical device can provide the user with an interface to view data of the medical device. As used herein, “communicatively coupled” can include coupled via various wired and/or wireless connections between devices such that data can be transferred in various directions between the devices. The coupling need not be a direct connection, and in some examples, can be an indirect connection. 
     In some examples, a computing system can include a mobile device that belongs to the user of the medical device. The mobile device (e.g., a smartwatch) can generate user visible data from a combination of inputs. In some examples, the mobile device can include a display. The display can be a touchscreen display that serves as an input device. When a touchscreen display is touched by a finger, digital pen (e.g., stylus), or other input mechanism, associated data can be received, displayed, and/or transmitted by the mobile device. The touchscreen display may include pictures and/or words, among others that a user can touch to interact with data, the medical device, other computing devices, and/or the mobile device. 
     The inputs can include data such as settings of the medical device, current user physical data, cloud data, medical device identification data, medical device manufacturing data, biometric data of the user, environmental data, etc. Biometric data can include a height, weight, blood type, heart rate, blood pressure, glucose levels, a level of molecules, chemical compounds, (e.g., drugs, alcohol, etc.) in the blood of the user, histamine production, antibody production, among others. Environmental data can include a geographical location, air pollution information, allergen information, ultraviolet radiation, among others. 
     In one example embodiment, the mobile device can analyze the data from the medical device by comparing the input data to data generated by the medical device in real time. The analyzed data can be presented on the display of the mobile device. Based on the analysis, the mobile device can take an action. For example, the mobile device can transmit an electronic notification to another computing device corresponding to a user, and/or a medical facility. In some examples a user can interact with the display of the mobile device to transmit the analyzed data to another computing device, to an emergency contact entity (e.g., another person, or emergency services, etc.). In another example, based on the analysis, the mobile device can initiate the action absent user interaction with the display, a preventative action to the medical device, or initiate an alarm on the mobile device to alert the user to a result of the analysis. 
     Additionally, the mobile device can monitor trends in the data generated by the medical device and update the data as the trends change. The trends can be displayed on the display of the mobile device. For example, a medical metric such as an electrocardiogram (EKG) of a first person may not be the same as an EKG of a second person. By receiving real-time data from a medical device, a trend that is specific to a user of the medical device can be established by the mobile device and therefore reported to a user. 
     In another example embodiment, the data can be analyzed by a different memory device and/or controller. The different memory device can be included in network relationship such as a cloud communicatively coupled to the mobile device. The cloud can store data about the medical device, data about the user such as historical data, etc. The memory device of the cloud can analyze the data about the medical device by comparing the data received about the medical device and data generated by the medical device. Based on the comparison, the memory device of the cloud can transmit a signal to the mobile device, and the mobile device can initiate a preventative action to the medical device or initiate an alarm on the mobile device to alert the user to a result of the analysis. 
     In the following detailed description of the present disclosure, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration how one or more embodiments of the disclosure can be practiced. These embodiments are described in sufficient detail to enable those of ordinary skill in the art to practice the embodiments of this disclosure, and it is to be understood that other embodiments can be utilized and that process, electrical, and structural changes can be made without departing from the scope of the present disclosure. 
     As used herein, designators such as “N,” “M,” “P,” “Q,” etc., particularly with respect to reference numerals in the drawings, indicate that a number of the particular feature so designation can be included. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms “a,” “an,” and “the” can include both singular and plural referents, unless the context clearly dictates otherwise. In addition, “a number of,” “at least one,” and “one or more” (e.g., a number of memory devices) can refer to one or more memory devices, whereas a “plurality of” is intended to refer to more than one of such things. Furthermore, the words “can” and “may” are used throughout this application in a permissive sense (i.e., having the potential to, being able to), not in a mandatory sense (i.e., must). The term “include,” and derivations thereof, means “including, but not limited to.” The terms “coupled,” and “coupling” mean to be directly or indirectly connected physically or for access to and movement (transmission) of commands and/or data, as appropriate to the context. The terms “data” and “data values” are used interchangeably herein and can have the same meaning, as appropriate to the context. 
     The figures herein follow a numbering convention in which the first digit or digits correspond to the figure number and the remaining digits identify an element or component in the figure. Similar elements or components between different figures can be identified by the use of similar digits. For example,  106  can reference element “ 06 ” in  FIG. 1 , and a similar element can be referenced as  206  in  FIG. 2 . A group or plurality of similar elements or components can generally be referred to herein with a single element number. For example, a plurality of reference elements  430 - 1 , . . . ,  430 -N (e.g.,  430 - 1  to  430 -N) can be referred to generally as  430 . As will be appreciated, elements shown in the various embodiments herein can be added, exchanged, and/or eliminated so as to provide a number of additional embodiments of the present disclosure. In addition, the proportion and/or the relative scale of the elements provided in the figures are intended to illustrate certain embodiments of the present disclosure and should not be taken in a limiting sense. 
       FIG. 1  is a functional block diagram in the form of a computing system  100  including an apparatus in the form of a mobile device  102  in accordance with a number of embodiments of the present disclosure. As used herein, an “apparatus” can refer to, but is not limited to, any of a variety of structures or combinations of structures, such as a circuit or circuitry, a die or dice, a module or modules, a device or devices, or a system or systems, for example. The mobile device  102  can include a memory device  112  and a controller  110 . 
     The memory device  112  can include different types of memory. There are many different types of memory including volatile and non-volatile memory. For example, non-volatile memory can provide persistent data by retaining written data when not powered, and non-volatile memory types can include NAND flash memory, NOR flash memory, read only memory (ROM), Electrically Erasable Programmable ROM (EEPROM), Erasable Programmable ROM (EPROM), and Storage Class Memory (SCM) that can include resistance variable memory, such as phase change random access memory (PCRAM), three-dimensional cross-point memory (e.g., 3D XPoint™), resistive random access memory (RRAM), ferroelectric random access memory (FeRAM), magnetoresistive random access memory (MRAM), and programmable conductive memory, among other types of memory. Volatile memory can require power to maintain its data (e.g., host data, error data, etc.), and volatile memory types can include random-access memory (RAM), dynamic random access memory (DRAM), and static random access memory (SRAM), among others. 
     The mobile device  102  can be a computing device. Some examples of a computing device are a wearable computing device (e.g., a smartwatch, smart glasses, etc.), a personal laptop computer, a tablet, a phablet, a desktop computer, a computing device located in a vehicle, a digital camera, a mobile telephone (e.g., a smartphone), an internet-of-things (IoT) enabled device, a memory card reader, or graphics processing unit (e.g., a video card), among various other types of computing devices. The mobile device  102  can include a system motherboard and/or backplane and can include a number of memory access devices such as a number of processing resources (e.g., one or more processors, microprocessors, image processor, and/or some other type of controlling circuitry). One of ordinary skill in the art will appreciate that “a processor” can intend one or more processors, such as a parallel processing system, a number of coprocessors, etc. 
     As used herein an “IoT enabled device” can refer to devices embedded with electronics, software, sensors, actuators, and/or network connectivity which enable such devices to connect to a network and/or exchange data. Examples of IoT enabled devices include mobile phones, smart phones, tablets, phablets, computing devices, implantable devices, vehicles, home appliances, smart home devices, monitoring devices, wearable devices, devices enabling intelligent shopping systems, among other cyber-physical systems. 
     The mobile device  102  can include a display  109 . The display  109  may be a touchscreen display of the mobile device  102  such as a smartwatch. The controller  110  can be communicatively coupled to the memory device  112  and/or the display  109 . The display  109  can display analyzed data to a user of the medical device  104 . The display  109  can provide real-time information to the user of the medical device. As will be further described in connection with  FIG. 3 , the display  109  can display a number of options to transmit the analyzed data and/or to inform the user of the analyzed data. The mobile device  102  can be coupled to other computing devices  114 - 1  to  114 -M. Some examples of the other computing devices  114  include a computing device included in a medical facility such as a hospital, a different mobile device related to the user of the medical device  104  (e.g., computing device of an emergency contact person), among others. 
     As illustrated in  FIG. 1 , the mobile device  102  can include a display  109  and be coupled to a medical device  104 . In some embodiments, the medical device  104  can be an implantable medical device  104 . An implantable medical device can include a medical device that is in contact with a portion of a user&#39;s body such that is partially visible, completely visible, or not visible. An implantable medical device can include a medical device that is selectively removeable. Some examples, of medical devices include, implantable cardioverter defibrillators (ICDs), pacemakers, glucose detecting contact lenses, insulin pumps, cochlear implants, hearing aids, prothesis (e.g., implantable prothesis), a diaphragm pacing system, among others. 
     The medical device  104  can transmit data  106 - 1  to  106 -N as indicated by the arrow  120 . The data  106 - 1  may be baseline dataset. As used herein, a baseline dataset can include identification data about the medical device (e.g., manufacturing information, serial number, etc.). A baseline dataset can also include information about the user of the medical device  104 . For example, the baseline dataset can include information related to a user of the medical device  104 , where the information is related to at least one of family history, geographic location, a health of the user, habits of the user, or any combination thereof. The data  106 - 1  can be displayed on the display  109 . 
     The medical device  104  can generate and transmit different data  106 -N. The different data  106 -N can be displayed on the display  109 . The different data  106 -N can include data collected by the medical device  104  as the medical device  104  is operating. For example, the medical device  104  may be an ICD, and the different data  106 -N generated may be heartrate information (e.g., an EKG). The different data  106 -N can be transmitted during a predetermined intervals, or during predetermined periods of time, or combinations thereof. The medical device  104  can transmit the data  106 - 1  to the mobile device  102  as indicated by the arrow  122  and can transmit the different data  106 -N as indicated by the arrow  124 . 
     In an example embodiment, and as illustrated in  FIG. 1 , the mobile device  102  can include a controller  110  coupled to a memory device  112 . The controller  110  can be configured to receive the data  106 - 1  from the medical device  104  where the data  106 - 1  is baseline dataset related to the medical device  104  and/or the user of the medical device  104 . For example, the medical device  104  can be an implantable medical device  104  and the data  106 - 1  from the medical device  104  is at least one of an identifier of the medical device  104  (e.g., manufacturer information), an identifier of a user of the medical device  104  (e.g., name, address, emergency contact information), a medical facility associated with the medical device  104  (e.g., doctor and/or hospital information), family history of the user of the medical device  104 , or combinations thereof. The controller  110  can store the data  106 - 1  in the memory device  112 . 
     Continuing with the above example, the controller  110  can be configured to receive different data  106 -N from the medical device  104 , where the different data  106 -N is received from the medical device  104  as the different data  106 -N is generated by the medical device  104 . The data  106 - 1  and the different data  106 -N can be displayed on the display  109 . For instance, a medical device  104  such as an ICD may monitor the heartbeat of the user in which the ICD is implanted. The ICD may generate data  106 -N about the heartbeats and transmit them to the mobile device  102  periodically, consistently, during predetermined intervals, and/or during predetermined periods of time, etc. and the generated data  106 N can be visible on the display  109 . The controller  110  can store the different data  106 -N in the memory device  112 . Because the mobile device  102  has received and stored the data  106 - 1  (e.g., the baseline dataset) and the different data  106 -N in the memory device  112 , the controller  110  can analyze the data  106 - 1  from the medical device  104  and the different data  106 -N generated by the medical device  104 . 
     For example, the analysis can include a comparison of the data  106 - 1  and the different data  106 -N. The controller  110  can be configured with one or more thresholds that can determine how the comparison can affect the medical device. In other examples, the controller  110  can analyze the different data  106 -N by comparing it to the one or more configured thresholds. For example, the controller  110  can compare the received different data  106 -N with the one or more thresholds and initiate an action based on the different data being above or below a determined threshold. In some examples, the threshold may be determined based at least in part on the data  106 - 1  (e.g., the baseline dataset). For instance, the baseline dataset can inform the controller  110  what sufficient homeostasis is for the user of the medical device  104 . Because the medical device  104  is transmitting data  106 - 1  and different data  106 -N the controller  110  can establish what is typical for the user of the medical device  104  and establish thresholds accordingly. 
     The analyzed data can be presented on the display  109  of the mobile device  102  such that a user can view the analyzed data. In some examples, the user may select from options visible on the display  109 . For example, the controller  110  can perform an action based on input received from a user selecting an option from the display  109 . The controller  110  can perform an action  108  based on the analyzed data  106 - 1  from the medical device  104  and the different data  106 -N generated by the medical device  104 . An action  108  can be a notification, and the notification can be transmitted to a computing device  114  (as indicated by the arrow  128 ) and include information about the medical device  104 . The notification may be an electronic notification such as a text message, an email, an automated phone call, a social media message, etc. The notification can be transmitted to a computing device  114  such as a computing device within a medical facility, a computing device  114  belonging to an emergency contact determined by the controller  110  receiving the baseline dataset, and/or a computing device belonging to the user of the medical device  104  (e.g., a separate computing device than the mobile device  102 ). 
     In another example embodiment, the action  108  is an alarm (transmitted as indicated by the arrow  130 ), and the alarm is generated by the mobile device  102  in the form of an audible signal, a vibration, an electronic communication, an electric shock, or any combination thereof. For instance, in an example where the mobile device  102  is a smartwatch worn by the user of the medical device  104 , the alarm can be generated by the smartwatch such that the user is made aware of the alarm. Said differently, the medical device  104  can be an ICD implanted in a user, and the action  108  can be an alarm of the smartwatch worn by the user. In this way, the user received real-time data about the medical device  104  and can view the real-time data on the display  109 . In other examples, the action  108  is a signal transmitted (as indicated by the arrow  126 ) to the medical device  104 , and the medical device  104  generates electricity (or another operation, releases medication, glucose, insulin, etc.) responsive to the receipt of the signal. 
     In a non-limiting example, the medical device  104  can be an ICD and the action  108  can initiate a delivery of an electric shock by the ICD. For instance, in an example where the medical device  104  is an ICD, the action  108  can include transmitting a signal from the mobile device  102  to the medical device  104  to initiate an electric shock to the user of the implanted medical device  104  (e.g., the ICD). In another non-limiting example, the medical device  104  can be an insulin pump (or glucose pump) and the action  108  can initiate a delivery of insulin and/or glucose by the insulin pump. 
     In another example embodiment, the action  108  can include and/or initiate updating the baseline data stored by the memory device  112 . As mentioned above, the controller  110  can be configured to store the baseline dataset in the memory device  112  coupled to the mobile device and update the baseline dataset based at least in part on the different data  106 -N received from the medical device  104 , the action  108 , or both. 
       FIG. 2  is a functional block diagram in the form of a computing system  201  including a mobile device  202  and a plurality of memory devices in accordance with a number of embodiments of the present disclosure. The mobile device  202  includes a controller  210 , a memory device  212 , and a display  209  which can be analogous to the mobile device  102 , the controller  110 , the display  109 , and the memory device  112  described in connection with  FIG. 1 . The mobile device  202  can be coupled to a medical device  204  which can be analogous to the medical device  104  of  FIG. 1 . The medical device  204  can transmit data  206 - 1  and different data  206 -N as indicated by the arrow  220  and can be analogous to the data  106 - 1  and the different data  106 -N. The mobile device  202  can be coupled to one or more other computing devices  214 - 1  and/or  214 -M which can be analogous to the other computing devices  114  described in connection with  FIG. 1 . The mobile device  202  can be further coupled to a different memory device  208 . The different memory device  208  may be in a wired or wireless network relationship with the mobile device  202  and/or the other computing devices  214 . 
     As used herein, the term “network relationship” can, for example, refer to a local area network (LAN), VLAN, wide area network (WAN), personal area network (PAN), a distributed computing environment (e.g., a cloud computing environment), storage area network (SAN), Metropolitan area network (MAN), a cellular communications network, and/or the Internet, among other types of network relationships. In some embodiments, the different memory device  208  can be included on a network device such as a server computing device (e.g., on-premise server, private, public, or hybrid cloud server) that comprises a hardware or a combination of hardware and software that can process and/or display network-related information. In some implementations, a network device may refer to an access point acting as a virtual master network controller among a cluster of access points. The different memory device  208  can include circuitry and/or logic to store the data  206 - 1 , the different data  206 -N, and/or to perform analysis on the respective data. 
     For example, the mobile device  202  may be a smartwatch worn by a user of the medical device  204 , where the medical device  204  is implanted in the user. The smartwatch can include a display  209  to provide real-time data about the implanted medical device  204  to the user. The user can utilize the smartwatch to transmit data  206 - 1  (e.g., baseline data) via the display  209 , the different data  206 -N (e.g., data as it is generated by the medical device), to the different memory device  208 . In some incidences, the mobile device  202  may be relatively small (e.g., a smartwatch) and the memory device  212  may not have the capacity to store all of the data generated by the medical device  204 . As such, the mobile device  202  may be in a network relationship with a different memory device  208  which can increase storage capacity. 
     For example, the computing system  201  can include a memory device  212  coupled to a controller  210  included in a mobile device  202 . The medical device  204  can be coupled to the mobile device  202 , where the medical device  204  is to provide information about the medical device  204  to the mobile device  202  where the medical device  204  is implantable. The mobile device can include a display  209  to provide the user of the medical device  204  with the data  206 - 1 , the different data  206 -N, and/or analyzed data. A different memory device  208  can be coupled to the mobile device  202  to receive the information about the medical device  204  from the mobile device  202 . 
     The controller  210  can be configured to receive data  206 - 1  from the medical device  204  (as indicated by the arrow  222 ), where the controller  210  can store the data  206 - 1  (e.g., baseline dataset) in the memory device  212  coupled to the controller  210  as a baseline dataset related to the medical device  204 . The controller  210  can transmit the data  206 - 1  from the medical device  204  to the different memory device  208 . In some examples, the user can transmit the data  206 - 1  from the mobile device  202  to the different memory device  208  by selecting an option on the display  209 . The different memory device  208  can store the baseline dataset. 
     The controller  210  can receive different data  206 -N (as indicated by the arrow  224 ) from the medical device  204 , where the different data  206 -N can be received from the medical device  204  as the different data  206 -N is generated by the medical device  204 . Said differently, as the medical device  204  generate data (e.g., heartbeat, blood sugar levels, etc.) about the user and/or the medical device  204 , the medical device  204  can transmit the different data  206 -N as it is generated. In this way, the user of the mobile device  202  can receive real-time data about the medical device  204 . In some examples, the user can transmit the different data  206 -N from the mobile device  202  to the different memory device  208  by selecting an option on the display  209 . The controller  210  can transmit the different data  206 -N from the medical device  204  to the different memory device  208 . 
     As mentioned, the different memory device  208  may include a capacity to store a larger amount of data when compared to the memory device  212  of the mobile device  202  (e.g., a smartwatch). The different memory device  208  may store historical information related to a user of the medical device, where the information is can be related to at least one of family history, geographic location, a health of the user, habits of the user, or any combination thereof. In some examples, the user can input the historical data into the mobile device  202  using the display  209  and transmit the historical data to the different memory device  208  using the display  209 . 
     The different memory device  208  can perform an analysis of the data  206 - 1  and the different data  206 -N. The analysis can include a comparison of the data  206 - 1 , to the different data  206 -N, and/or any historical information as mentioned above. The different memory device  208  can transmit the analyzed data to the mobile device  202 . The transmitted analyzed data can be visible to the user on the display  209  as the user receives the analyzed data. For example, the different memory device  208  can push a notification (e.g., a text message, an email, etc.) related to the medical device  204  to the mobile device  202  (e.g., a smartwatch) responsive to the analyzed data. The notification can be viewed by a user on the display  209 . In this way, the user of the medical device  204  wearing the smartwatch can receive real time data about the medical device  204 . 
     The controller  210  can receive the analyzed data from the different memory device  208  responsive to it performing an analysis on the data  206 - 1  from the medical device  204  and the different data  206 -N generated by the medical device  204 . The controller  210  can initiate an action  208  based on the analyzed data received from the different memory device  208 . In some examples, the action can be selected from the display  209  by the user. An action  208  can be a notification, and the notification can be transmitted to a computing device  214  (as indicated by the arrow  228 ) and include information about the medical device  204 . The notification may be an electronic notification such as a text message, an email, an automated phone call, a social media message, etc. The notification can be transmitted to a computing device  214  such as a computing device within a medical facility, a computing device belonging to an emergency contact determined by the controller  210  receiving the baseline dataset, and/or a computing device  214  belonging to the user of the medical device  204  (e.g., a separate computing device than the mobile device  202 ). In another example embodiment, the action  208  is an alarm (transmitted as indicated by the arrow  230 ), and the alarm is generated by the mobile device  202  in the form of an audible signal, a vibration, an electronic communication, an electric shock, or any combination thereof. In other examples, the action  208  is a signal transmitted (as indicated by the arrow  226 ) to the medical device  204 . In some examples, the signal transmitted to the medical device  204  initiates the medical device  204  to administer medication (e.g., insulin from an insulin pump, etc.). 
     In some examples, embodiments, the action  208  can include the controller  210  initiating an update to the baseline dataset based on the analyzed data, the action  208 , or both. For example, the mobile device  202  may generate an action  208  in the form of an alarm. A user may indicate that the alarm is not necessary, and the baseline data can be updated to reflect that the analyzed data resulted in an unnecessary alarm. In some examples, the update to the baseline dataset can include changing the thresholds. These methods can provide a user of the medical device  204  with real-time data from the medical device  204  as the user operates in their daily life. 
       FIG. 3  is a diagram  317  representing an example display  309  of a mobile device  302  for medical device data analysis in accordance with a number of embodiments of the present disclosure.  FIG. 3  includes a user  321  utilizing a wearable mobile device  302  in the form of a smartwatch. The mobile device  302  is communicatively coupled to a medical device  304  as indicated by the arrow  329 . The mobile device  302  and the medical device  304  can be analogous to the mobile device  102  and the medical device  104  of  FIG. 1 . The medical device  304  may be an implantable medical device implanted into the user  321 . The mobile device  302  may be communicatively coupled to a computing device  314 - 1  included in a medical facility  319  and a computing device  314 -M related to an emergency contact person. The mobile device  302  can be communicatively coupled to a different memory device  308  which can be analogous to the different memory device  208  of  FIG. 2 . 
       FIG. 3  illustrates a display  309  of the mobile device  302 . For clarity and understanding of the detailed description, the display  309  is enlarged. The display  309  can include options for the user to select based on data related to the medical device  304 . For example, data (e.g., the data  106 - 1  and/or the different data  106 -N) can be generated by the medical device  304  and transmitted to the mobile device  302  as indicated by the arrow  329 . The mobile device  302  can analyze the data using a controller analogous to the controller  110  of  FIG. 1 . The analyzed data  327  can be visible on the display  309 . The user  321  can view the analyzed data  327  and initiate an action using the display  309 . 
     For example, the user  321  can initiate an action by selecting the option for the medical facility  325 - 1  and the mobile device can transmit the analyzed data  327  to the computing device  314 - 1  included in the medical facility  319  as indicated by the arrow  328 - 1 . In some examples, the mobile device  302  transmits the data generated by the medical device  304  to the different memory device  308  for analysis as indicated by the arrow  326 , and the mobile device  302  can display the data analyzed by the different memory device  308  to on the display  309 . 
     In another non-limiting embodiment, the user  321  can initiate an action by selecting the option for the different memory device  325 - 2  and the mobile device can transmit the analyzed data  327  to the different memory device  325 - 2  to be stored. In some examples, a medical facility related to the user may have access to the different memory device  308 . In some examples, the mobile device  302  transmits the data generated by the medical device  304  to the different memory device  308  for analysis as indicated by the arrow  326 , and the mobile device  302  can display the data analyzed by the different memory device  308  to on the display  309 . 
     In another non-limiting embodiment, the user  321  can initiate an action by selecting the option for the emergency contact  325 - 3  and the mobile device  302  can transmit the analyzed data  327  to the computing device  314 -M corresponding to the emergency contact  323  as indicated by the arrow  328 -Q. In some examples, the emergency contact may be a person known to the user  321 . In some examples, the computing device  314 -M may be a different mobile device belonging to the emergency contact. In some examples, the mobile device  302  transmits the data generated by the medical device  304  to the different memory device  308  for analysis as indicated by the arrow  326 , and the mobile device  302  can display the data analyzed by the different memory device  308  to on the display  309 . 
     In another non-limiting embodiment, the user  321  can initiate an action by selecting the option for the preventative action  325 - 4  and the mobile device  302  can transmit a signal to the medical device  304  as indicated by the arrow  329  to initiate the preventative action. In some examples, the preventive action is a signal to the medical device to administer an electronic shock, glucose, and/or insulin, or other medications. In some examples, the preventative action may be an alarm or an alert to the user. For example, if the medical device  304  is a device to monitor heartrate, the preventive action may be an alert to suggest to the user  321  to rest when the heartrate is above or below a threshold. 
     In another non-limiting embodiment, the user  321  can initiate an action by selecting the option to update a baseline dataset and the mobile device  302  can update a baseline dataset or alter a threshold based on the user interacting with the display  309  to update the baseline dataset. For example, if the user  321  moves to a different climate with different environmental conditions, the user  321  can update the baseline dataset based on the analyzed data  327 . 
       FIG. 4  is a flow diagram  403  representing an example of medical device data analysis in accordance with a number of embodiments of the present disclosure. The flow diagram  403  describes a medical device (e.g., the medical device  104  described in connection with  FIG. 1 ). The medical device can be an implantable medical device and can transmit data (e.g., the data  106 - 1  and/or the different data  106 -N of  FIG. 1 ) to a mobile device (e.g., the mobile device  102  of  FIG. 1 ). In some examples, the mobile device can be a smartwatch and can include a display (e.g., the display  309  of  FIG. 3 ). In some examples, the mobile device can transmit the data and/or different data to a different memory device (e.g., the different memory device  208  of  FIG. 2 ) for analysis. In some examples, the different memory device is wirelessly coupled to the mobile device and performs the analysis on the respective data by comparing the baseline dataset to the different data generated by the medical device. The analysis may cause a controller (e.g., the controller  110  of  FIG. 1 ) to update the baseline dataset. 
     For example, at  430 , the controller and/or the different memory device networked with the controller can receive data from the medical device. The data received can be a baseline dataset and/or different data that was transmitted as it was generated by the medical device. At block  432  the controller and/or the different memory device can analyze the respective data and compare the baseline dataset to different data generated by the medical device. The comparison can determine trends in the data of the medical device. 
     For example, if the medical device is an ICD implanted in a user, initial baseline datasets may include a particular heartrate, and as time passes, the ICD can generate heartbeat data that can be compared to the baseline particular heartbeat data and actions (e.g., an action  108  of  FIG. 1 ) can be initiated based on the comparison. However, the user may change their lifestyle that results in different baseline datasets. For example, if the user begins exercising on a regular basis, the baseline dataset may change because the heartrate of the user may change. In this example, at block  434  the controller and/or the different memory device can update the baseline dataset responsive to the comparison of the baseline dataset to the different data generated by the medical device. In this way, the comparison of the baseline dataset and the data generated by the ICD may be updated. 
     In other examples, the baseline dataset may not be updated because the comparison resulted in an analysis that was not consistent with a trend. For instance, if the user has a problematic heart episode, the controller may initiate an action (e.g., an electric shock). In this incidence, the baseline dataset would not be updated as it is not indicative of a regular trend. In other words, at block  436 , the controller and/or the different memory device can refrain from updating the baseline dataset responsive to the comparison of the baseline dataset to the different data generated by the medical device. 
       FIG. 5  is a flow diagram representing an example method  505  for medical device data analysis in accordance with a number of embodiments of the present disclosure. At block  540 , the method  505  can include receiving, by a mobile device (e.g., the mobile device  102  of  FIG. 1 ) coupled to a medical device (e.g., the medical device  104  of  FIG. 1 ), data (e.g., the data  106 - 1  of  FIG. 1 ) from the medical device, wherein the data is a part of a baseline dataset related to the medical device. The medical device can be implanted in a person and can be wirelessly coupled to the mobile device. The baseline dataset can include identification data about the medical device (e.g., manufacturing information, serial number, etc.). A baseline dataset can also include information about the user of the medical device. Different data (e.g., the different data  106 -N of  FIG. 1 ) can be received by the mobile device. Data generated by the medical device can be viewed by a user on a display (e.g., the display  309  of  FIG. 3 ). 
     For example, at block  542 , the method  505  includes receiving different data from the medical device, wherein the different data is received from the medical device as the different data is generated by the medical device. The different data can be data transmitted to the mobile device in real-time. In this way, a user of the medical device can view respective data about the medical device. The controller (e.g., the controller  110  of  FIG. 1 ) of the mobile device may analyze the different data as it is received by the mobile device. 
     For example, at block  544 , the method  505  includes analyzing the data from the medical device and the different data generated by the medical device. The baseline dataset may determine a threshold related to the medical device. The analysis of the different data can include the controller comparing the different data received form the medical device to a threshold established by the baseline dataset. The controller may initiate an action based on the analysis. 
     For example, at block  546 , the method  505  includes performing an action based on the analyzed data from the medical device and the different data generated by the medical device. The action can be performed at the mobile device or medical device, or both. In an example embodiment, the action can include transmitting the analyzed data to a computing device (e.g., the computing device  114 - 1  of  FIG. 1 ), where the computing device is within a medical center. The analyzed data can be transmitted to a computing device that is associated with a medical center related to the user of the medical device. In this example, the real-time data generated by the medical device can be reported to a medical center. In another example embodiment, the action can include transmitting the analyzed data to another mobile device (e.g., the computing device  114 -M of  FIG. 1 ) corresponding to a user of the medical device. 
     In this example, the computing device may be a mobile device related to an emergency contact of the user and the real-time data generated by the medical device can be transmitted to another person in the event that the user of the medical device is incapacitated. In yet another example embodiment, the action can include assessing a health of a user of the medical device responsive to the analyzed data and initiating an operation of the medical device based on the assessment. In this example, the controller can initiate an operation of the medical device (e.g., the dispensing of insulin, or an electric shock. 
       FIG. 6  is a flow diagram representing an example method  607  for medical device data analysis in accordance with a number of embodiments of the present disclosure. At block  660 , the method  607  includes receiving, by a mobile device (e.g., the mobile device  102  of  FIG. 1 ) coupled to a medical device (e.g., the medical device  104  of  FIG. 1 ), data from the medical device, wherein the data is a baseline dataset related to the medical device. The medical device can be implanted in a person and can be wirelessly coupled to the mobile device. Data generated by the medical device can be viewed by a user on a display (e.g., the display  309  of  FIG. 3 ). 
     At block  662 , the method  607  includes transmitting, from the mobile device, the data from the medical device to a different memory device (e.g., the different memory device  208  of  FIG. 2 ) wirelessly coupled to the mobile device. In some examples, the different memory device wirelessly coupled to the mobile device is located on a private cloud and communicatively coupled to at least one of the medical device, a computing device of a medical facility (e.g., the computing device  114  of  FIG. 1 ), or both. 
     At block  664 , the method  607  includes, receiving, by the mobile device, different data (e.g., the different data  106 -N) from the medical device, wherein the different data is received as the different data is generated by the medical device. In this way, real-time data can be received by the mobile device (e.g., a smartwatch worn by the user of the medical device). 
     At block  666 , the method  607  includes, transmitting, from the mobile device, the different data from the medical device to the different memory device wirelessly coupled to the mobile device. The mobile device can transmit the different data to the different memory device for analysis. 
     At block  668 , the method  607  includes receiving, by the mobile device, analyzed data from the different memory device wirelessly coupled to the mobile device and responsive to the different memory device wirelessly coupled to the mobile device performing an analysis on the data from the medical device. The different memory device can perform the analysis and provide the analyzed data to the mobile device to initiate an action (e.g., the action  108  of  FIG. 1 ). 
     At block  670 , the method  607  includes performing an action based on the analyzed data from the medical device and the different data generated by the medical device. The action can be performed at the mobile device or medical device, or both. In some examples, based on the analysis, the mobile device can initiate a preventative action to the medical device, or initiate an alarm on the mobile device to alert the user to a result of the analysis. 
     Although specific embodiments have been illustrated and described herein, those of ordinary skill in the art will appreciate that an arrangement calculated to achieve the same results can be substituted for the specific embodiments shown. This disclosure is intended to cover adaptations or variations of one or more embodiments of the present disclosure. It is to be understood that the above description has been made in an illustrative fashion, and not a restrictive one. Combination of the above embodiments, and other embodiments not specifically described herein will be apparent to those of skill in the art upon reviewing the above description. The scope of the one or more embodiments of the present disclosure includes other applications in which the above structures and processes are used. Therefore, the scope of one or more embodiments of the present disclosure should be determined with reference to the appended claims, along with the full range of equivalents to which such claims are entitled. 
     In the foregoing Detailed Description, some features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the disclosed embodiments of the present disclosure have to use more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.