Medical device data analysis

Abstract

This describes systems, apparatus, and methods related to data analysis of medical devices. In some instances, a medical device is implanted in a user of the medical device, and the user does not have easy access to the data generated by the medical device. In one example, a controller may be configured to receive data from the medical device by a mobile device coupled to the medical device, wherein the data is part of a baseline dataset associated with the medical device. The controller may be configured to: receive dissimilar data from the medical device, wherein the dissimilar data is received from the medical device when the medical device generates the dissimilar data; analyze the data from the medical device and the dissimilar data generated by the medical device; and perform actions based on the analyzed data and the dissimilar data generated by the medical device.

Description

Technical Field

[0001] This disclosure generally relates to semiconductor memories and methods, and more specifically, to apparatus, systems and methods for data analysis of medical devices. Background Technology

[0002] Medical devices (e.g., implantable medical devices, medical prostheses, etc.) can communicate with scanners, servers, wireless devices, etc., to obtain and exchange information. Medical devices can be implanted in patients to affect their biological and / or additional functions. Over time, the patient's needs or the impact of the medical device on the patient may change. To avoid adverse effects of medical devices on patients, for example, communication with external devices can be used to check the medical device to improve operational efficiency and more closely match the patient's needs or the doctor's advice.

[0003] Memory devices can be coupled to other devices (e.g., computing devices, mobile devices, etc.) to store (e.g., write) data, commands, and / or instructions for use by the device when the device's computer or electronic system is running. For example, data, commands, and / or instructions can be transferred between the host and the memory device during operation of the computing or other electronic system.

[0004] Memory devices are typically provided as internal semiconductor integrated circuits in computers or other electronic systems. Many different types of memory exist, including volatile and non-volatile memory. Volatile memory may require power to retain 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 provides permanent data by retaining the stored data when no power is supplied and can include NAND flash memory, NOR flash memory, and resistive 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. Attached Figure Description

[0005] Figure 1 This is a functional block diagram in the form of a computing system according to several embodiments of the present disclosure, the computing system including a device in the form of a mobile device.

[0006] Figure 2 This is a functional block diagram in the form of a computing system according to several embodiments of the present disclosure, the computing system including a mobile device and a plurality of memory devices.

[0007] Figure 3 This is a diagram illustrating an example display of a mobile device for medical device data analysis according to several embodiments of the present disclosure.

[0008] Figure 4 This is a flowchart illustrating an example of medical device data analysis according to several embodiments of the present disclosure.

[0009] Figure 5 This is a flowchart illustrating an example method for data analysis of a medical device according to several embodiments of the present disclosure.

[0010] Figure 6 This is a flowchart illustrating an example method for data analysis of a medical device according to several embodiments of the present disclosure. Detailed Implementation

[0011] This describes systems, apparatus, and methods related to data analysis of medical devices. Medical devices can generate data about the user of the medical device and / or the medical device itself. In some instances, the medical device is implanted in the user of the medical device, and the user does not have easy access to the data generated by the medical device. The medical device can be coupled to a computing system 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, making the user able to access said information. In an example, a controller can be configured to receive data from the medical device by a mobile device coupled to the medical device, wherein the data is part of a baseline dataset associated with the medical device. The controller can be configured to: receive different data from the medical device, wherein different data is received from the medical device when 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 actions based on the analyzed data and the different data generated by the medical device.

[0012] As used herein, storing data may involve writing data to a memory medium contained in a memory device. For example, data can be stored in a memory device by writing data to the memory medium of the memory device. Additionally, data can be retrieved from its storage location by a computing device (e.g., a mobile device and / or a controller). Medical devices may generate data about a user's health status, the user's body parts, and / or the medical device itself. Data generated by a medical device may be difficult for the user of the medical device to view and / or analyze.

[0013] In some prior methods, data generated by a medical device (e.g., an implantable medical device) can be viewed by the user of the medical device in the presence of a physician and / or in a medical facility setting. Medical devices may contain limited memory storage capacity, so in some cases, data generated by the medical device may not be stored by the medical device unless the data is deemed problematic. However, users of medical devices may want to know the effects of the medical device on their bodies when performing harmless 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 daily activities. Furthermore, in some cases, users may experience superficial minor accidents (e.g., minor falls) and want to know if the medical device has recorded any abnormalities (e.g., problems). The inability to view data in real time can lead to frustration, wasted time, anxiety, and / or wasted resources traveling to a medical facility to find that the medical device has not stored any information about superficial minor accidents.

[0014] Conversely, as will be described herein, communicatively coupling a medical device to a user's computing system (e.g., a mobile device) corresponding to the medical device provides the user with an interface to view data from the medical device. As used herein, "communicatively coupled" can include coupling via various wired and / or wireless connections between devices to allow data to be transmitted between devices in various directions. The coupling need not be a direct connection, and in some instances, can be an indirect connection.

[0015] In some instances, the computing system may include a mobile device belonging to a user of the medical device. The mobile device (e.g., a smartwatch) may generate user-visible data from combinations of inputs. In some instances, the mobile device may include a display. The display may be a touchscreen display acting as an input device. When a finger, digital pen (e.g., a stylus), or other input device touches the touchscreen display, the mobile device may receive, display, and / or transmit associated data. The touchscreen display may include images and / or text that the user can touch to interact with data, the medical device, other computing devices, and / or the mobile device.

[0016] Inputs may include data such as the environment of the medical device, current user physical data, cloud data, medical device identification data, medical device manufacturing data, user biometric data, and environmental data. Biometric data may include height, weight, blood type, heart rate, blood pressure, glucose levels, molecular levels in the user's blood, compounds (such as drugs, alcohol), histamine production, antibody production, etc. Environmental data may include geographical location, air pollution information, allergen information, and ultraviolet radiation.

[0017] In one example embodiment, the mobile device can analyze data from a medical device by comparing input data with data generated in real time by the medical device. The analyzed data can be displayed on the mobile device's screen. Based on the analysis, the mobile device can take action. For example, the mobile device can transmit electronic notifications to another computing device corresponding to the user and / or the medical institution. In some instances, the user can interact with the mobile device's screen to transmit the analyzed data to another computing device, an emergency contact entity (e.g., another person or emergency services), etc. In another instance, based on the analysis, the mobile device can initiate actions without user interaction with the screen, preventative actions against the medical device, or issue an alert on the mobile device to notify the user of the analysis results.

[0018] Furthermore, mobile devices can monitor trends in data generated by medical devices and update the data as trends change. These trends can be displayed on the mobile device's screen. For example, the medical indicators of an individual's electrocardiogram (EKG) may differ from those of a second individual. By receiving real-time data from the medical device, user-specific trends can be established by the mobile device and thus reported to the user.

[0019] In another embodiment, data can be analyzed via different storage devices and / or controllers. These different storage devices may be included in a network relationship, such as a cloud communicatively coupled to a mobile device. The cloud may store data about the medical device, data about the user (e.g., historical data), etc. The cloud's storage devices can analyze data about the medical device by comparing data received by the medical device with data generated by the medical device. Based on this comparison, the cloud's storage devices can transmit signals to the mobile device, and the mobile device can initiate preventative actions against the medical device or issue an alarm on the mobile device to alert the user of the analysis results.

[0020] In the following detailed description of this disclosure, reference is made to the accompanying drawings, which form a part of this disclosure, and the drawings illustrate by way of illustration one or more embodiments of this disclosure. These embodiments are described in sufficient detail to enable those skilled in the art to practice embodiments of this disclosure, and it should be understood that other embodiments may be utilized and process, electrical, and structural changes may be made without departing from the scope of this disclosure.

[0021] As used herein, designators such as “N,” “M,” “P,” and “Q,” which are specific reference numerals in the drawings, indicate the number of particular features that may be included. It should also 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, unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “the” may include both singular and plural references. Additionally, “a plurality,” “at least one,” and “one or more” (e.g., a plurality of memory devices) may refer to one or more memory devices, while “a plurality” is intended to mean more than one of such things. Furthermore, the words “may” and “can” are used throughout this application in a permissive sense (i.e., having the potential to be possible) rather than in a mandatory sense (i.e., must). The term “comprising” and its derivatives mean “including but not limited to.” Depending on the context, the term “coupled / coupling” means physically directly or indirectly connected or accessing and moving (transmitting) commands and / or data. Depending on the context, the terms “data” and “data value” are used interchangeably and may have the same meaning in this document.

[0022] The diagrams in this document follow a numbering rule, where the first one or more digits correspond to the diagram number, and the remaining digits identify the elements or components within the diagram. Similar elements or components between different diagrams can be identified using similar digits. For example, 106 can be referenced. Figure 1 Component "06" in the text, and similar components in Figure 2 The symbol 206 may be used. Generally, a single element number may be used herein to refer to a group or number of similar elements or components. For example, multiple reference elements 430-1, ..., 430-N (e.g., 430-1 to 430-N) may generally be referred to as 430. As will be understood, elements shown in the various embodiments herein may be added, interchanged, and / or removed to provide multiple additional embodiments of this disclosure. Furthermore, the scale and / or relative dimensions of the elements provided in the figures are intended to illustrate certain embodiments of this disclosure and should not be construed as limiting.

[0023] Figure 1 This is a functional block diagram in the form of a computing system 100 according to several embodiments of the present disclosure, the computing system including a device in the form of a mobile device 102. As used herein, "device" may refer to, but is not limited to, any of a variety of structures or combinations thereof, such as a circuit or circuit system, one or more dies, one or more modules, one or more devices, or one or more systems. The mobile device 102 may include a memory device 112 and a controller 110.

[0024] Memory device 112 may include different types of memory. Many different types of memory exist, including volatile and non-volatile memory. For example, non-volatile memory provides permanent data by retaining written data when no power is supplied, and non-volatile memory types may include NAND flash memory, NOR flash memory, read-only memory (ROM), electrically erasable programmable ROM (EEPROM), erasable programmable ROM (EPROM), and memory-type memory (SCM) that may include resistive variable memory, such as phase-change random access memory (PCRAM), three-dimensional crosspoint memory (e.g., 3DXPoint™), resistive random access memory (RRAM), ferroelectric random access memory (FeRAM), magnetoresistive random access memory (MRAM), and programmable conductive memory, as well as other types of memory. Volatile memory may require power to maintain its data (e.g., host data, error data, etc.), and volatile memory types may include random access memory (RAM), dynamic random access memory (DRAM), and static random access memory (SRAM), etc.

[0025] Mobile device 102 may be a computing device. Some examples of computing devices are wearable computing devices (e.g., smartwatches, smart glasses, etc.), personal laptops, tablet computers, phablets, desktop computers, computing devices located in vehicles, digital cameras, mobile phones (e.g., smartphones), Internet of Things (IoT) enabled devices, memory card readers, or graphics processing units (e.g., video cards), and various other types of computing devices. Mobile device 102 may include a system motherboard and / or backplane, and may include multiple memory access devices, such as multiple processing resources (e.g., one or more processors, microprocessors, image processors, and / or some other type of control circuitry). Those skilled in the art will understand that "processor" may mean one or more processors, such as parallel processing systems, multiple coprocessors, etc.

[0026] As used herein, "IoT-enabled device" can mean a device embedded with electronics, software, sensors, actuators, and / or network connectivity that enables such device to connect to a network and / or exchange data. Examples of IoT-enabled devices include mobile phones, smartphones, tablet computers, phablets, computing devices, implantable devices, vehicles, home appliances, smart home devices, monitoring devices, wearable devices, devices enabling smart shopping systems, and other cyber-physical systems.

[0027] Mobile device 102 may include display 109. Display 109 may be, for example, a touchscreen display of mobile device 102 such as a smartwatch. Controller 110 may be communicatively coupled to memory device 112 and / or display 109. Display 109 may display analyzed data to the user of medical device 104. Display 109 may provide real-time information to the user of medical device 104. (The last sentence appears to be incomplete and possibly refers to a different device.) Figure 3 Further description: the display 109 may display multiple options to transmit the analyzed data and / or notify the user of the analyzed data. The mobile device 102 may be coupled to other computing devices 114-1 to 114-M. Some examples of other computing devices 114 include computing devices contained in medical facilities such as hospitals, various mobile devices associated with the user of the medical device 104 (e.g., computing devices for emergency contacts), etc.

[0028] like Figure 1 As described, mobile device 102 may include display 109 and be coupled to medical device 104. In some embodiments, medical device 104 may be an implantable medical device. Implantable medical devices may include medical devices that partially contact the user's body, making them partially visible, fully visible, or invisible. Implantable medical devices may include selectively removable medical devices. Some examples of medical devices include implantable cardioverter defibrillators (ICDs), pacemakers, glucose-detecting contact lenses, insulin pumps, cochlear implants, hearing aids, prostheses (e.g., implantable prostheses), diaphragmatic pacing systems, and the like.

[0029] Medical device 104 can transmit data 106-1 to 106-N, as indicated by arrow 120. Data 106-1 may be a baseline dataset. As used herein, the baseline dataset may contain identifying data about the medical device (e.g., manufacturing information, serial number, etc.). The baseline dataset may also contain information about the user of medical device 104. For example, the baseline dataset may contain information related to the user of medical device 104, wherein the information is related to at least one of family history, geographic location, user health status, user habits, or any combination thereof. Data 106-1 may be displayed on display 109.

[0030] Medical device 104 can generate and transmit various data 106-N. The various data 106-N can be displayed on display 109. The various data 106-N can include data collected by medical device 104 when it is in operation. For example, medical device 104 can be an ICD, and the generated various data 106-N can be heart rate information (e.g., EKG). The various data 106-N can be transmitted during predetermined intervals, during predetermined time periods, or combinations thereof. Medical device 104 can transmit data 106-1 to mobile device 102 as indicated by arrow 122, and can transmit various data 106-N as indicated by arrow 124.

[0031] In the example embodiments and as Figure 1 As described herein, mobile device 102 may include a controller 110 coupled to memory device 112. Controller 110 may be configured to receive data 106-1 from medical device 104, wherein data 106-1 is a baseline dataset associated with medical device 104 and / or its user. For example, medical device 104 may be an implantable medical device, and data 106-1 from medical device 104 may be at least one of the following: an identifier of medical device 104 (e.g., manufacturer information), an identifier of the user of medical device 104 (e.g., name, address, emergency contact information), a medical institution associated with medical device 104 (e.g., doctor and / or hospital information), the user's family history, or a combination thereof. Controller 110 may store data 106-1 in memory device 112.

[0032] Continuing with the above example, controller 110 can be configured to receive different data 106-N from medical device 104, wherein different data 106-N is received from medical device 104 when medical device 104 generates different data 106-N. Data 106-N and different data 106-N can be displayed on display 109. For example, medical device 104, such as with an ICD, can monitor the heartbeat of a user with an implanted ICD. The ICD can generate data 106-N about the heartbeat and periodically, consistently, at predetermined intervals and / or during predetermined time periods, transmit the data to mobile device 102, and the generated data 106-N can be seen on display 109. Controller 110 can store different data 106-N in memory device 112. Because the mobile device 102 has received data 106-1 (e.g., baseline dataset) and different data 106-N and stored them 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.

[0033] For example, the analysis may include comparing data 106-1 and different data 106-N. The controller 110 may be configured with one or more thresholds to determine how the comparison will affect the medical device. In other instances, the controller 110 may analyze the different data by comparing the different data 106-N with one or more configured thresholds. For example, the controller 110 may compare the received different data 106-N with one or more thresholds and initiate action based on whether the different data is above or below a determined threshold. In some instances, the threshold may be determined at least in part based on data 106-1 (e.g., a baseline dataset). For example, the baseline dataset may inform the controller 110 what is sufficient steady state 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 may establish typical content for the user of the medical device 104 and establish thresholds accordingly.

[0034] The analyzed data can be presented on the display 109 of the mobile device 102, allowing the user to view the analyzed data. In some instances, the user can select from options visible on the display 109. For example, the controller 110 can perform an action based on input received from the 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 different data 106-N generated by the medical device 104. Action 108 can be a notification, and the notification can be transmitted to the computing device 114 (as indicated by arrow 128) and the notification contains information about the medical device 104. The notification can be an electronic notification, such as a text message, email, automated phone call, social media message, etc. The notification can be transmitted to the computing device 114, such as a computing device within a medical facility, a computing device 114 belonging to an emergency contact identified by the controller 110 that receives the baseline dataset, and / or a computing device belonging to a user of the medical device 104 (e.g., a computing device separate from the mobile device 102).

[0035] In another embodiment, action 108 is an alarm (transmitted as indicated by arrow 130), and the alarm is generated by mobile device 102 in the form of an audible signal, vibration, electronic communication, electric shock, or any combination thereof. For example, in an instance where mobile device 102 is a smartwatch worn by a user of medical device 104, the alarm may be generated by the smartwatch to make the user aware of the alarm. In other words, medical device 104 may be an ICD implanted in the user, and action 108 may be an alarm from a smartwatch worn by the user. In this way, the user receives real-time data about medical device 104 and can view the real-time data on display 109. In other embodiments, action 108 is a signal transmitted (as indicated by arrow 126) to medical device 104, and medical device 104 generates electricity (or another operation, releases medication, glucose, insulin, etc.) in response to receiving the signal.

[0036] In a non-limiting example, medical device 104 may be an ICD, and action 108 may initiate the delivery of an electric shock via the ICD. For example, in an instance where medical device 104 is an ICD, action 108 may include transmitting a signal from mobile device 102 to medical device 104 to initiate an electric shock to a user of the implanted medical device 104 (e.g., an ICD). In another non-limiting example, medical device 104 may be an insulin pump (or glucose pump), and action 108 may initiate the delivery of insulin and / or glucose by the insulin pump.

[0037] In another example embodiment, action 108 may include and / or initiate an update of baseline data stored in memory device 112. As mentioned above, controller 110 may be configured to store the baseline dataset in memory device 112 coupled to the mobile device, and update the baseline dataset at least in part based on different data 106-N received from medical device 104, action 108, or both.

[0038] Figure 2 This is a functional block diagram in the form of a computing system 201 according to several embodiments of the present disclosure, the computing system including a mobile device 202 and a plurality of memory devices. The mobile device 202 includes components that can be similarly combined with… Figure 1 The described mobile device 102, controller 110, display 109, and memory device 112 include controller 210, memory device 212, and display 209. Mobile device 202 can be coupled to medical device 204, which may be similar to... Figure 1 Medical device 104. Medical device 204 can transmit data 206-1 and different data 206-N as indicated by arrow 220, and said data and different data can be similar to data 106-1 and different data 106-N. Mobile device 202 can be coupled to a device that can be similarly combined with Figure 1The other computing device 114 described includes one or more other computing devices 214-1 and / or 214-M. The mobile device 202 may be further coupled to different memory devices 208. The different memory devices 208 may be in a wired or wireless network relationship with the mobile device 202 and / or other computing devices 214.

[0039] As used herein, the term "network relationship" may refer, for example, to a local area network (LAN), VLAN, wide area network (WAN), personal area network (PAN), distributed computing environment (e.g., cloud computing environment), storage area network (SAN), metropolitan area network (MAN), cellular communication network, and / or the Internet, as well as other types of network relationships. In some embodiments, different storage devices 208 may be included on a network device, such as server computing devices (e.g., local servers, dedicated, public, or hybrid cloud servers) that include hardware or a combination of hardware and software capable of processing and / or displaying network-related information. In some embodiments, a network device may refer to an access point that acts as a virtual master network controller in an access point cluster. Different storage devices 208 may include circuitry and / or logic for storing data 206-1, different data 206-N, and / or for performing analysis on the corresponding data.

[0040] For example, mobile device 202 may be a smartwatch worn by a user of medical device 204, wherein medical device 204 is implanted in the user. The smartwatch may include a display 209 to provide the user with real-time data about the implanted medical device 204. The user can use the smartwatch to transfer data 206-1 (e.g., baseline data) via the display 209, and different data 206-N (e.g., data generated by the medical device) to different storage devices 208. In some cases, mobile device 202 may be relatively small (e.g., a smartwatch), and storage device 212 may not have the capacity to store all the data generated by medical device 204. Therefore, mobile device 202 may be networked with different storage devices 208 that can increase storage capacity.

[0041] For example, computing system 201 may include memory device 212 coupled to controller 210 included in mobile device 202. Medical device 204 may be coupled to mobile device 202, wherein medical device 204 provides information about medical device 204 to the implantable mobile device 202. Mobile device may include display 209 to provide data 206-1, different data 206-N, and / or analyzed data to a user of medical device 204. Different memory devices 208 may be coupled to mobile device 202 to receive information about medical device 204 from mobile device 202.

[0042] Controller 210 can be configured to receive data 206-1 from medical device 204 (as indicated by arrow 222), wherein controller 210 may store data 206-1 (e.g., a baseline dataset) in a memory device 212 coupled to controller 210 as a baseline dataset associated with medical device 204. Controller 210 may transfer data 206-1 from medical device 204 to a different memory device 208. In some instances, a user may transfer data 206-1 from mobile device 202 to a different memory device 208 by selecting an option on display 209. The different memory device 208 may store the baseline dataset.

[0043] The controller 210 can receive different data 206-N from the medical device 204 (as indicated by arrow 224), wherein different data 206-N can be received from the medical device 204 as the medical device 204 generates different data 206-N. In other words, when the medical device 204 generates data about the user and / or the medical device 204 (e.g., heart rate, blood glucose level, etc.), the medical device 204 can transmit the different data 206-N as it generates the different data. In this way, the user of the mobile device 202 can receive real-time data about the medical device 204. In some instances, the user can transfer different data 206-N from the mobile device 202 to different memory devices 208 by selecting an option on the display 209. The controller 210 can transfer different data 206-N from the medical device 204 to different memory devices 208.

[0044] As mentioned, the different memory device 208 may include capacity for storing a larger amount of data 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 the user of the medical device, wherein the information may be related to at least one of family history, geographic location, the user's health status, the user's habits, or any combination thereof. In some instances, the user may use the display 209 to input historical data into the mobile device 202 and use the display 209 to transfer historical data to the different memory device 208.

[0045] Different memory devices 208 can perform analysis of data 206-1 and different data 206-N. The analysis may include comparisons of data 206-1 with different data 206-N and / or any historical information as mentioned above. Different memory devices 208 can transmit the analyzed data to mobile device 202. When a user receives the analyzed data, the transmitted analyzed data is visible to the user on display 209. For example, different memory devices 208 can push notifications (e.g., text messages, emails, etc.) related to medical device 204 to mobile device 202 (e.g., a smartwatch) in response to the analyzed data. The user can view the notifications on display 209. In this way, a user of medical device 204 wearing a smartwatch can receive real-time data about medical device 204.

[0046] Controller 210 may receive analyzed data from different memory devices 208 in response to performing analysis on data 206-1 from medical device 204 and different data 206-N generated by medical device 204. Controller 210 may initiate action 208 based on the analyzed data received from different memory devices 208. In some instances, the action may be selected by a user from display 209. Action 208 may be a notification, and the notification may be transmitted to computing device 214 (as indicated by arrow 228) and the notification may contain information about medical device 204. The notification may be an electronic notification, such as a text message, email, automated telephone call, social media message, etc. The notification may be transmitted to computing device 214, such as a computing device within a medical facility, a computing device belonging to an emergency contact identified by controller 210 that receives the baseline dataset, and / or a computing device 214 belonging to a user of medical device 204 (e.g., a computing device separate from mobile device 202). In another embodiment, action 208 is an alarm (transmitted as indicated by arrow 230), and the alarm is generated by the mobile device 202 in the form of an audible signal, vibration, electronic communication, electric shock, or any combination thereof. In other embodiments, action 208 is a signal transmitted (as indicated by arrow 226) to medical device 204. In some embodiments, the signal transmitted to medical device 204 activates medical device 204 to administer medication (e.g., insulin from an insulin pump).

[0047] In some implementations, action 208 may include controller 210 initiating an update to the baseline dataset based on the analyzed data, action 208, or both. For example, mobile device 202 may generate action 208 in the form of an alarm. The user may indicate that an alarm is not needed and may update the baseline data to reflect that the analyzed data results in an unnecessary alarm. In some instances, updating the baseline dataset may involve changing a threshold. These methods can provide users of medical device 204 with real-time data from medical device 204 as the user operates in their daily life.

[0048] Figure 3 Figure 317 is an example display 309 representing a mobile device 302 for medical device data analysis according to several embodiments of the present disclosure. Figure 3 This 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 arrow 329. The mobile device 302 and the medical device 304 may be similar to... Figure 1 The mobile device 302 and medical device 104 are described. Medical device 304 may be an implantable medical device implanted in user 321. Mobile device 302 may be communicatively coupled to computing device 314-1 and computing device 314-M associated with emergency contacts, both contained in medical facility 319. Mobile device 302 may also be communicatively coupled to various memory devices 308, which may be similar to... Figure 2 Different memory devices 208.

[0049] Figure 3 The display 309 of the mobile device 302 is illustrated. For clarity and understanding of the specific implementation, the display 309 is enlarged. The display 309 may include options for a user to select based on data associated with the medical device 304. For example, data (e.g., data 106-1 and / or different data 106-N) may be generated by the medical device 304 and transmitted to the mobile device 302, as indicated by arrow 329. The mobile device 302 may use a similar... Figure 1 The controller 110 analyzes the data. The analyzed data 327 is visible on the display 309. The user 321 can view the analyzed data 327 and initiate actions using the display 309.

[0050] For example, user 321 can initiate an action by selecting the option of medical facility 325-1, and the mobile device can transmit the analyzed data 327 to the computing device 314-1 contained in medical facility 319, as indicated by arrow 328-1. In some instances, mobile device 302 transmits data generated by medical device 304 to different memory devices 308 for analysis, as indicated by arrow 326, and mobile device 302 can display the data analyzed by the different memory devices 308 on display 309.

[0051] In another non-limiting embodiment, user 321 can initiate an action by selecting an option for different storage devices 325-2, and the mobile device can transfer the analyzed data 327 to different storage devices 325-2 for storage. In some instances, a medical institution associated with the user can access different storage devices 308. In some instances, mobile device 302 transfers data generated by medical device 304 to different storage devices 308 for analysis, as indicated by arrow 326, and mobile device 302 can display the data analyzed by different storage devices 308 on display 309.

[0052] In another non-limiting embodiment, user 321 can initiate action by selecting an option for emergency contact 325-3, and mobile device 302 can transmit the analyzed data 327 to computing device 314-M corresponding to emergency contact 323, as indicated by arrows 328-Q. In some instances, the emergency contact may be an individual known to user 321. In some instances, computing device 314-M may be different mobile devices belonging to the emergency contact. In some instances, mobile device 302 transmits data generated by medical device 304 to different memory devices 308 for analysis, as indicated by arrow 326, and mobile device 302 can display the data analyzed by the different memory devices 308 on display 309.

[0053] In another non-limiting embodiment, user 321 may initiate an action by selecting an option for preventative action 325-4, and mobile device 302 may transmit a signal to medical device 304 as indicated by arrow 329 to initiate the preventative action. In some instances, the preventative action is a signal arriving at the medical device to administer an electric shock, glucose and / or insulin, or other medication. In some instances, the preventative action may be an alarm or warning to the user. For example, if medical device 304 is a heart rate monitoring device, the preventative action may be a warning advising user 321 to rest when the heart rate is above or below a threshold.

[0054] In another non-limiting embodiment, user 321 can initiate an action by selecting an option to update the baseline dataset, and mobile device 302 can update the baseline dataset or change a threshold based on user interaction with display 309 to update the baseline dataset. For example, if user 321 moves to a different climate with different environmental conditions, user 321 can update the baseline dataset based on analyzed data 327.

[0055] Figure 4 This is a flowchart 403 illustrating an example of data analysis using a medical device according to several embodiments of the present disclosure. Flowchart 403 describes a medical device (e.g., in conjunction with...) Figure 1 The described medical device 104). The medical device may be an implantable medical device and may transmit data (e.g., Figure 1 Data 106-1 and / or different data 106-N) are transmitted to a mobile device (e.g., Figure 1 Mobile device 102). In some instances, the mobile device may be a smartwatch and may include a display (e.g., Figure 3 The display 309). In some instances, the mobile device can transfer data and / or different data to different memory devices (e.g., display 309). Figure 2 Different memory devices 208) are used for analysis. In some instances, different memory devices are wirelessly coupled to a mobile device, and analysis is performed on the corresponding data by comparing a baseline dataset with different data generated by a medical device. The analysis can enable a controller (e.g., Figure 1 The controller 110 updates the baseline dataset.

[0056] For example, at box 430, the controller and / or different memory devices networked with the controller can receive data from the medical device. The received data may be a baseline dataset and / or different data transmitted during generation by the medical device. At box 432, the controller and / or different memory devices can analyze the relevant data and compare the baseline dataset with the different data generated by the medical device. The comparison can determine trends in the data from the medical device.

[0057] For example, if the medical device is an ICD implanted in the user, the initial baseline dataset may contain a specific heart rate, and over time, the ICD can generate heart rate data that can be compared to the baseline specific heart rate data, and actions can be initiated based on the comparison (e.g., Figure 1(Action 108). However, users may change their lifestyles, resulting in different baseline datasets. For example, if a user starts exercising regularly, the baseline dataset may change because the user's heart rate may change. In this example, at box 434, the controller and / or different storage devices may update the baseline dataset in response to a comparison with different data generated by the medical device. In this way, the baseline dataset and the comparison of data generated by the ICD can be updated.

[0058] In other instances, the baseline dataset may not be updated because comparisons could produce analyses that do not reflect a trend. For example, if a user has a problematic heart attack, the controller could initiate an action (e.g., an electric shock). In this case, the baseline dataset would not be updated because it does not indicate a regular trend. In other words, at box 436, the controller and / or different memory devices can avoid updating the baseline dataset in response to comparisons with different data generated by the medical device.

[0059] Figure 5 This is a flowchart illustrating an example method 505 for data analysis of a medical device according to several embodiments of the present disclosure. At block 540, method 505 may include a device coupled to a medical device (e.g., Figure 1 The mobile device of the medical device 104) (e.g., Figure 1 The mobile device 102) receives data from the medical device (e.g., Figure 1 Data 106-1, wherein the data is part of a baseline dataset relating to a medical device. The medical device may be implanted in an individual and may be wirelessly coupled to a mobile device. The baseline dataset may contain identifying data about the medical device (e.g., manufacturing information, serial number, etc.). The baseline dataset may also contain information about the user of the medical device. Different data (e.g., ...) may be received by the mobile device. Figure 1 Different data 106-N). Data generated by the medical device can be displayed by the user on a monitor (e.g., Figure 3 View on monitor 309.

[0060] For example, at box 542, method 505 includes receiving different data from a medical device, wherein different data is received from the medical device when the medical device generates different data. The different data may be data transmitted to a mobile device in real time. In this way, the user of the medical device can view relevant data about the medical device. When different data is received by the mobile device, the controller of the mobile device (e.g., Figure 1 The controller 110 can analyze the different data.

[0061] For example, at box 544, method 505 includes analyzing data from a medical device and different data generated by the medical device. A baseline dataset can determine thresholds related to the medical device. The analysis of the different data may include the controller comparing the different data received from the medical device with the thresholds established from the baseline dataset. The controller may initiate an action based on the analysis.

[0062] For example, at block 546, method 505 includes performing an action based on analyzed data from a medical device and different data generated by the medical device. The action can be performed on a mobile device or a medical device, or both. In an example embodiment, the action may include transferring the analyzed data to a computing device (e.g., Figure 1 The computing device 114-1 is located within a medical center. The analyzed data can be transmitted to a computing device associated with the medical center, which is associated with the user of the medical device. In this example, real-time data generated by the medical device can be reported to the medical center. In another embodiment, the action may include transmitting the analyzed data to another mobile device corresponding to the user of the medical device (e.g., [missing information]). Figure 1 (Computing device 114-M).

[0063] In this example, the computing device may be a mobile device associated with the user's emergency contact, and in the event that the user of the medical device becomes incapacitated, real-time data generated by the medical device can be transmitted to another person. In yet another example embodiment, the action may include assessing the user's health status in response to the analyzed data and initiating an operation of the medical device based on the assessment. In this example, the controller may initiate an operation of the medical device (e.g., insulin dispensing or electric shock).

[0064] Figure 6 This is a flowchart illustrating an example method 607 for data analysis of a medical device according to several embodiments of the present disclosure. At block 660, method 607 includes a process coupled to a medical device (e.g., Figure 1 The mobile device of the medical device 104) (e.g., Figure 1 The mobile device 102 receives data from the medical device, wherein the data is a baseline dataset associated with the medical device. The medical device can be implanted in a person and can be wirelessly coupled to the mobile device. The data generated by the medical device can be displayed by the user on a display (e.g., ...). Figure 3 View on monitor 309.

[0065] At box 662, method 607 includes transferring data from a medical device from a mobile device to a different memory device wirelessly coupled to the mobile device (e.g., ...). Figure 2Different memory devices 208). In some instances, different memory devices wirelessly coupled to a mobile device reside on a dedicated cloud and communicatively coupled to a medical device, a computing device of a medical institution (e.g., Figure 1 The computing device 114), or at least one of the two.

[0066] At box 664, method 607 includes receiving different data (e.g., different data 106-N) from the medical device by a mobile device, wherein different data is received when the medical device generates different data. In this way, real-time data can be received by a mobile device (e.g., a smartwatch worn by the user of the medical device).

[0067] At box 666, method 607 includes transferring different data from a medical device from a mobile device to different memory devices wirelessly coupled to the mobile device. The mobile device can transfer the different data to the different memory devices for analysis.

[0068] At box 668, method 607 includes receiving analyzed data from different memory devices wirelessly coupled to the mobile device, and performing analysis on data from the medical device in response to the different memory devices wirelessly coupled to the mobile device. The different memory devices can perform the analysis and provide the analyzed data to the mobile device to initiate actions (e.g., Figure 1 Action 108).

[0069] At box 670, method 607 includes performing actions based on analyzed data from the medical device and different data generated by the medical device. The actions can be performed on a mobile device, a medical device, or both. In some instances, based on the analysis, the mobile device can initiate preventative actions against the medical device, or issue an alert on the mobile device to notify the user of the analysis results.

[0070] While specific embodiments have been shown and described herein, those skilled in the art will understand that arrangements calculated to achieve the same results may replace the specific embodiments shown. This disclosure is intended to cover modifications or variations of one or more embodiments of this disclosure. It should be understood that the above description has been carried out illustratively and not restrictively. Combinations of the above embodiments and other embodiments not specifically described herein will be apparent to those skilled in the art upon review of the above description. The scope of one or more embodiments of this disclosure includes other applications in which the above structures and processes are used. Therefore, the scope of one or more embodiments of this disclosure should be determined with reference to the appended claims together with the full scope of the equivalents given by such claims.

[0071] In the foregoing detailed embodiments, some features are grouped together in a single embodiment for the purpose of simplification. This approach of the present disclosure should not be construed as reflecting an intention that the disclosed embodiments must use more features than expressly stated in each claim. In fact, as reflected in the appended claims, the subject matter of the invention lies in less than all the features of a single disclosed embodiment. Therefore, the appended claims are hereby incorporated into the detailed embodiments, wherein each claim is an independent embodiment.

Claims

1. A medical system comprising: A mobile device including a smartwatch and coupled to a memory device (112, 212), the smartwatch including a display, and the memory device including instructions executable to cause the mobile device to: Data (106-1, 206-1) is received from a medical device (104, 204, 304), the medical device including an implantable cardioverter defibrillator (ICD) coupled to the memory device, wherein the data is a baseline associated with the medical device and includes a threshold steady-state level from the user for establishing a baseline user health dataset, and further includes identification data about the medical device, the user's family history, the geographical location of the medical device, the user's health status, and the user's habits; Configure the threshold based on the aforementioned steady-state threshold level; Receive different data (106-N, 206-N) from the medical device, wherein the different data is received from the medical device when the medical device generates the different data; The data from the medical device and the different data generated by the medical device are analyzed by comparing them with the configured threshold. Based on the analyzed data from the medical device and the different data generated by the medical device, trends specific to the user of the medical device are established. The established trend is displayed via the display of the smartwatch; as well as The delivery of an action to the medical device, including an electric shock via the ICD, is initiated via the display of the smartwatch based on the established trend, the analyzed data from the medical device, the configured threshold, and the different data generated by the medical device. The medical device is configured to: Receive the action; as well as The electric shock is applied to the user based on the established trend, the analyzed data from the medical device, and the different data generated by the medical device. as well as The memory device is configured such that the mobile device: Monitor the different data generated by the implanted medical device, compare the configured threshold of the baseline dataset with the different data, and update the baseline dataset in response to the comparison between the baseline dataset and the different data; The different data are used to determine the emergency contacts who need to be notified to the user. as well as Send the notification to the emergency contact.

2. The medical system of claim 1, wherein the data from the medical device is an identifier of the medical device, an identifier of the user of the medical device, a medical institution associated with the medical device, the family history of the user of the medical device, or any combination thereof.

3. The medical system according to claim 1, wherein: The action further includes transmitting signals (126, 226) to the medical device; and The medical device generates electricity in response to receiving the signal.

4. The medical system according to claim 1, wherein: The actions further include alarms; and The alarm is generated by the device in the form of an audible signal, vibration, electronic communication, or any combination thereof.

5. The medical system according to claim 1, wherein: The action further includes notification; and The notification is transmitted to a computing device and contains information about the medical device.

6. A medical system (201) comprising: A memory device (212) coupled to a mobile device (202, 302) including a smartwatch, the smartwatch including a display; A medical device (204, 304) coupled to the mobile device, wherein the medical device includes an implantable cardioverter defibrillator (ICD) and provides information about the medical device to the mobile device, and wherein the medical device is implantable; Different memory devices (208, 308) are coupled to the mobile device, which is configured to: Receive the information about the medical device from the mobile device; Analysis is performed on the data received from the medical device by comparing it with a configured threshold steady-state level; as well as Analysis is performed on different data generated by the medical device by comparing them with a configured threshold. The mobile device is configured to: The data (206-1) is received from the medical device, wherein the data is stored in the memory device as a baseline dataset, the data includes a threshold steady-state level from the user for establishing a baseline user health dataset, and further includes identification data about the medical device, the user's family history, the geographical location of the medical device, the user's health status and the user's habits; The threshold is configured based on the steady-state level of the threshold; The data is transferred from the medical device to the different memory devices; The different data (206-N) are received from the medical device, wherein the different data are received from the medical device when the medical device generates the different data; The different data are transferred from the medical device to the different memory devices; In response to the different memory devices performing analysis on the data from the medical device and performing analysis on the different data generated by the medical device, the analyzed data is received from the different memory devices; Based on the analyzed data from the different memory devices, the transmission of an action (208) is initiated via the display of the smartwatch, the action including an electric shock via the ICD; To establish trends specific to the users of the medical device based on the analyzed data from the medical device and the different data generated by the medical device; The established trend is displayed via the display of the smartwatch; Monitor the different data generated by the implanted medical device, compare the configured threshold of the baseline dataset with the different data, and update the baseline dataset in response to the comparison between the baseline dataset and the different data: The execution instructions instruct the medical device to apply the electric shock to the user based on the established trend, the analyzed data from the medical device, the configured threshold, and the different data generated by the medical device. The different data are used to determine the emergency contacts who need to be notified to the user. as well as Send the notification to the emergency contact; The medical device is configured to: Receive the action; as well as The electric shock is applied to the user based on the established trend, the analyzed data from the medical device, and the different data generated by the medical device.

7. The medical system according to claim 6, wherein: The mobile device is a smartwatch including a display (209, 309); and The action is initiated via the display.

8. The medical system of claim 7, wherein the medical device is implanted in a user (321), and the action further includes an alarm from the smartwatch worn by the user.

9. The medical system of claim 7, wherein the different memory devices push notifications about the medical device to the smartwatch in response to the analyzed data.

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