The present invention is generally related to health tracking based on wearable sensors and/or applications and related health self-management services.
Digital health programs typically are built based on static data structures or modules and sequential rules that govern the execution of the programs. Such modules may comprise electronic interventions (e.g., messaging or notifications) that are designed to influence a user towards healthy behavioral changes or lifestyle. A static module structure does not necessarily fit well with the lifestyle of an individual user and/or the dynamic changes in life situations and/or the environment around the user. A poor lifestyle-fit may lead to a low adherence, and hence effectiveness, of the digital health program. As an alternative to a fixed program, digital health programs may be designed that enable a user to stop a given module and possibly start it again later, but this does not remove the underlying problem that the module is not adapted to the user.
In one embodiment, a computer-implemented method for managing plural micromodules over time, each micromodule comprising plural nodes corresponding to electronic interventions that follow logically from one another to form a narrative or story, the method comprising: receiving inputs from one or more input sources, the input sources monitoring user behavior and associated contexts; monitoring each of the plural micromodules, each of the plural micromodules beginning with an opportunity and ending with an assessment, each of the plural micromodules comprising a score; updating the scores based on the received inputs; selecting which of at least one of the plural micromodules to provide to a user at any given moment in time based on a comparison of the scores and historical data; and providing the selected micromodule to the user.
These and other aspects of the invention will be apparent from and elucidated with reference to the embodiment(s) described hereinafter.
Many aspects of the invention can be better understood with reference to the following drawings, which are diagrammatic. The components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present invention. Moreover, in the drawings, like reference numerals designate corresponding parts throughout the several views.
Disclosed herein are certain embodiments of a micromodule management system, method, and computer readable medium (herein, also collectively referred to as a micromodule management system) that increases the persuasiveness of health program content by managing micromodules (each of which includes a chain of insights) based on module history and a human model to enhance the adaptiveness of the health program.
Digressing briefly, and as indicated above, the current digital health program approach uses static, somewhat illustratively-described as brick wall, modules to govern execution of the health program. For instance, one week may utilize an activity module, followed on the next week with the activity module, then a nutrition module the next week, followed again by an activity module. These modules hence are designed under the assumption of a static lifestyle and/or environment. As an alternative to brick wall-type health programs, certain embodiments of a micromodule management system provide for an open-ended service that is built around the lifestyle of the user and which dynamically takes into account changes in the environment and the behavior of the user.
The micromodules comprise chains of electronic interventions (equivalently, statements, messages, notifications, all used interchangeably herein) that collectively provide a logical narrative or story over time. Each of the micromodules comprises a collection of nodes or data structures that are arranged according to a plurality of possible different paths or chains. Measures (e.g., scores) for the micromodules are computed based on statistics computed over time for each of the micromodules. Measures that meet a predefined criteria (e.g., greater than other scores and/or greater or equal to a predetermined threshold) are used to select the next node, which may be for the same micromodule or a different micromodule. Note that selection criteria for the next node may include the above and one or more additional criteria, including personalized criteria, features that meet historical criteria, or based on context aware features. As a statement is selected from among plural statements listed for a given node statement table, the statement is provided (e.g., published to a user), input data is received over an interval of time, and measures are computed for the various micromodules to select a next node statement for publication as a notification, and so on until a target node is reached. In the meantime, each notification (e.g., the issued statement) that is presented to the user is a logical step towards influencing a user in partaking in activities that improve the likelihood that the user will reach his or her goal. When the collection of notifications, though published in temporally different intervals, are viewed as a whole, the resulting chain of notifications that make up a micromodule comprises a narrative. That is, the statements or notifications comprise a logical relationship and provide a user-perceivable trend or direction towards a goal. The ongoing narrative provides continual, logical feedback and/or encouragement in assisting and/or advising the user in advancing progress towards a given goal. Certain embodiments of a micromodule management system orchestrates the issuance of the notifications according to an open-ended service based on data from one or more input sources (e.g., wearable devices comprising sensors, electronics devices, network storage (e.g., databases), etc.) and historical data.
Having summarized certain features of a micromodule management system of the present disclosure, reference will now be made in detail to the description of a micromodule management system as illustrated in the drawings. While a micromodule management system will be described in connection with these drawings, there is no intent to limit notification systems to the embodiment or embodiments disclosed herein. For instance, though described in the context of health management services, certain embodiments of a micromodule management system may be used to improve engagement of a user in other contexts, including financial management, business management, and industrial control processing. Note that the phrase, health management, refers to a broad set of services including fitness, health, and well-being, and includes not only clinical healthcare, but also personal healthcare, including baby care, baby development/monitoring, oral hygiene, skin care, shaving, etc., in addition to coaching, fitness and/or sports training, etc. Further, although the description identifies or describes specifics of one or more embodiments, such specifics are not necessarily part of every embodiment, nor are all various stated advantages necessarily associated with a single embodiment or all embodiments. On the contrary, the intent is to cover all alternatives, modifications and equivalents included within the spirit and scope of the disclosure as defined by the appended claims. Further, it should be appreciated in the context of the present disclosure that the claims are not necessarily limited to the particular embodiments set out in the description.
Note that throughout the specification, electronic interventions, statements, insights, and notifications are used interchangeably, the use of the terms notification or electronic intervention herein generally signifying that the statement is presented (published) electronically to a user via a device. In one embodiment, notifications may comprise a statement, wherein the statement comprises a reference to user data and a behavioral goal of the user and optionally a user preference. Statements are in the form of data structures, and according to the present disclosure are configured to convey information related to a plausible observation directed to the behavior of the user. The statements according to the present disclosure may be further configured to convey health-related information of the user. The statements may be presented as a fact that the user already recognizes. Further, the statements may be presented as a revealing of a hidden behavior pattern with advice to the user to change behavior to a better direction (e.g., improve health). In some embodiments, the electronic interventions may trigger circuitry of another device to perform a function or alter function, including alarm circuitry (e.g., for initiating visual, audible, haptic feedback), prosthetic or equipment control circuitry (e.g., triggering faster or slower treadmill speeds, resistance changes, such as to weight resistance equipment), among others. Certain embodiments of a micromodule management system automatically generates a large number of statements that are meaningful in a particular program context and selects nodes to link to a preceding node from among plural possible predefined pathways, wherein when viewed from the collective outcome of the various published statements over a period of time, the resulting chain or micromodule provides insight to the user (e.g., as presented at a user device) based on the node arrangement in narrative form. Measures or scores (those two terms likewise used herein interchangeably, the scores generally a subset of measures) are used in the initial defining of the statements, the selection of a starting node, and in the selection of subsequent nodes of the chain or micromodule to form a narrative to be presented to the user. In one embodiment, an assessment of a score for each of the micromodules is performed regularly, with the assessment enabling a decision on the next node (and hence statement) to present. In one embodiment, the measures or scores are computed for each micromodule, the scores based on statistical and heuristic weighting rules, and statements are selected for micromodules that have high scores (and meet a threshold value) in reaching a particular goal.
The digital health program according to the present disclosure is an application designed to be implemented on a mobile device (e.g., user device) to monitor physiological or psychological signs of the user as well as to track the real-time activities of the user. The program may be a health-related program or a health-related application. The programs developed for those devices employ one or more recommender-type systems to analyze the profile of the user and the historical data associated with one or more micromodules, and provide various types of messages to the user, or recommend one or more resources to the user. The statements individually comprise one or more personalized insights of the health-related behavior of the user. The statements may be presented as one or more texts displayed or played on the user device, one or more graphical illustrations displayed on the user device, a content card comprising one or more texts displayed on the user device, a content card comprising integrated texts and graphical illustrations displayed on the user device, or any combinations thereof. The statements may be generated with respect to different objectives, for example, education, feedback on performance, insight, motivation, etc. A statement provides valuable feedback and inspiration to the user, and helps the user to choose new opportunities to form healthier behavior and habits. Accordingly, the micromodule management system can provide to the user, insightful information that is personalized for each individual user and has more impact on the behavior of the user given its reliance of various statistics and historical and user data.
Note that use of the terms, node or nodes, refers to logical constructs for describing the data structures (of the statements) and facilitating an understanding of the chaining of the data structures that comprise the statements into a micromodule.
Referring now to
Also, such data gathered by the wearable device 12 may be communicated (e.g., continually, periodically, and/or aperiodically, including upon request) to one or more electronics devices, such as the electronics device 14 or via the cellular/wireless network 16 to the computing system 20. Such communication may be achieved wirelessly (e.g., using near field communications (NFC) functionality, Bluetooth functionality, 802.11-based technology, etc.) and/or according to a wired medium (e.g., universal serial bus (USB), etc.). Further discussion of the wearable device 12 is described below in association with
The electronics device 14 may be embodied as a smartphone, mobile phone, cellular phone, pager, stand-alone image capture device (e.g., camera), laptop, workstation, among other handheld and portable computing/communication devices, including communication devices having wireless communication capability, including telephony functionality. It is noted that if the electronics device 14 is embodied as a laptop or computer in general, the architecture more resembles that of the computing system 20 shown and described in association with
The cellular/wireless network 16 may include the necessary infrastructure to enable cellular and/or wireless communications by the electronics device 14 and optionally the wearable device 12. There are a number of different digital cellular technologies suitable for use in the cellular network 16, including: GSM, GPRS, CDMAOne, CDMA2000, Evolution-Data Optimized (EV-DO), EDGE, Universal Mobile Telecommunications System (UMTS), Digital Enhanced Cordless Telecommunications (DECT), Digital AMPS (IS-136/TDMA), and Integrated Digital Enhanced Network (iDEN), among others. The cellular/wireless network 16 may include modems, routers, etc. to enable the wearable device 12 and/or electronics device 14 to access the Internet via a wireless network, including according to wireless fidelity (WiFi) specifications.
The wide area network 18 may comprise one or a plurality of networks that in whole or in part comprise the Internet. The electronics device 14 and optionally wearable device 12 access one or more of the devices of the computing system 20 via the Internet 18, which may be further enabled through access to one or more networks including PSTN (Public Switched Telephone Networks), POTS, Integrated Services Digital Network (ISDN), Ethernet, Fiber, DSL/ADSL, WiFi, among others.
The computing system 20 comprises one or more devices coupled to the wide area network 18, including one or more computing devices networked together, including an application server(s) and data storage. The computing system 20 may serve as a cloud computing environment (or other server network) for the electronics device 14 and/or wearable device 12, performing processing and data storage on behalf of (or in some embodiments, in addition to) the electronics devices 14 and/or wearable device 12. In one embodiment, the computing system 20 may be configured to be a backend server for a health program. The computing system 20 receives data collected via one or more of the wearable device 12 or electronics device 14 and/or other devices or applications, stores the received data in a data structure (e.g., user profile database, etc.), and generates the notifications for presentation to the user. The computing system 20 is programmed to handle the operations of one or more health or wellness programs implemented on the wearable device 12 and/or electronics device 14 via the networks 16 and/or 18. For example, the computing system 20 processes user registration requests, user device activation requests, user information updating requests, data uploading requests, data synchronization requests, etc. The data received at the computing system 20 may be a plurality of measurements pertaining to the parameters, for example, body movements and activities, heart rate, respiration rate, blood pressure, body temperature, light and visual information, etc. and the corresponding context. In some embodiments, the data received at the computing system 20 may include measured, monitored, and/or inputted interactions between two or more individuals, including mother and a baby. Such data may further be received from social media websites. Based on the data observed during a period of time and/or over a large population of users, the computing system 20 generates statements pertaining to each specific parameter, and provides the statements via the networks 16 and/or 18 as an ongoing narrative of statements or notifications for presentation on devices 12 and/or 14. In some embodiments, the computing system 20 is configured to be a backend server for a health-related program or a health-related application implemented on the mobile devices. The functions of the computing system 20 described above are for illustrative purpose only. The present disclosure is not intended to be limiting. The computing system 20 may be a general computing server or a dedicated computing server. The computing system 20 may be configured to provide backend support for a program developed by a specific manufacturer.
When embodied as a cloud service or services, the computing system 20 may comprise an internal cloud, an external cloud, a private cloud, or a public cloud (e.g., commercial cloud). For instance, a private cloud may be implemented using a variety of cloud systems including, for example, Eucalyptus Systems, VMWare vSphere®, or Microsoft® HyperV. A public cloud may include, for example, Amazon EC2®, Amazon Web Services®, Terremark®, Savvis®, or GoGrid®. Cloud-computing resources provided by these clouds may include, for example, storage resources (e.g., Storage Area Network (SAN), Network File System (NFS), and Amazon S3®), network resources (e.g., firewall, load-balancer, and proxy server), internal private resources, external private resources, secure public resources, infrastructure-as-a-services (IaaSs), platform-as-a-services (PaaSs), or software-as-a-services (SaaSs). The cloud architecture of the computing system 20 may be embodied according to one of a plurality of different configurations. For instance, if configured according to MICROSOFT AZURE™, roles are provided, which are discrete scalable components built with managed code. Worker roles are for generalized development, and may perform background processing for a web role. Web roles provide a web server and listen and respond for web requests via an HTTP (hypertext transfer protocol) or HTTPS (HTTP secure) endpoint. VM roles are instantiated according to tenant defined configurations (e.g., resources, guest operating system). Operating system and VM updates are managed by the cloud. A web role and a worker role run in a VM role, which is a virtual machine under the control of the tenant. Storage and SQL services are available to be used by the roles. As with other clouds, the hardware and software environment or platform, including scaling, load balancing, etc., are handled by the cloud.
In some embodiments, the computing system 20 may be configured into multiple, logically-grouped servers, referred to as a server farm. The computing system 20 may comprise plural server devices geographically dispersed, administered as a single entity, or distributed among a plurality of server farms, executing one or more applications on behalf of one or more of the devices 12 and/or 14. The devices of the computing system 20 within each farm may be heterogeneous. One or more of the devices of the computing system 20 may operate according to one type of operating system platform (e.g., WINDOWS NT, manufactured by Microsoft Corp. of Redmond, Wash.), while one or more of the other devices of the computing system 20 may operate according to another type of operating system platform (e.g., Unix or Linux). The devices of the computing system 20 may be logically grouped as a server farm that may be interconnected using a wide-area network (WAN) connection or medium-area network (MAN) connection. The devices of the computing system 20 may each be referred to as, and operate according to, a file server device, application server device, web server device, proxy server device, or gateway server device. In one embodiment, the computing system 20 provide an API or web interface that enables the devices 12 and/or 14 to communicate with the computing system 20. The computing system 20 may also be configured to be interoperable across other servers and generate statements in a format that is compatible with other programs. In some embodiments, one or more of the functionality of the computing system 20 may be performed at the respective devices 12 and/or 14. Further discussion of the computing system 20 is described below in association with
An embodiment of a micromodule management system may comprise the wearable device 12, the electronics device 14, and/or the computing system 20. In other words, one or more of the aforementioned devices 12, 14, and 20 may implement the functionality of the micromodule management system. For instance, the wearable device 12 may comprise all of the functionality of a micromodule management system, enabling the user to avoid the need for Internet connectivity and/or carrying a smartphone 14 around. In some embodiments, the functionality of the micromodule management system may be implemented using a combination of the wearable device 12 and the electronics device 14 and/or the computing system 20 (with or without the electronics device 14). For instance, the wearable device 12 and/or the electronics device 14 may present notifications via a user interface and provide sensing functionality, yet rely on remote data structures of the computing system 20 and remote processing of the computing systems 20.
As an example, the wearable device 12 may monitor activity of the user, and communicate context and the sensed parameters (e.g., location coordinates, motion data, physiological data, etc.) to one of the devices (e.g., the electronics device 14 and/or the computing system 20) external to the wearable device 12, the computing system 20 where all statement generation and publish selection is performed, and then each notification may be generated at one of the devices remote to the wearable device 12 and communicated back to the wearable device 12 for presentation according to a given temporal order (e.g., at different time intervals) relative to the presentation of other notifications. One benefit to the latter embodiment is that off-loading of the computational resources of the wearable device 12 is enabled, conserving power consumed by the wearable device 12. In some embodiments, the notifications may be presented by the wearable device 12 and/or the electronics device 14 and all other processing may be performed by the computing system 20, and in some embodiments, the notifications may be presented by the wearable device 12 and/or the electronics device 14 and all other processing performed by the electronics device 14, and in some embodiments, the notifications and processing may be entirely performed by the wearable device 12 and/or the electronics device 14. These and/or other variations are contemplated to be within the scope of the disclosure. For instance, in some embodiments, networks and devices associated with the micromodule management system may be configured to be the same for all users, or customized for a sub-population, including created separately for each user.
Attention is now directed to
The application software 30 comprises a plurality of software modules (e.g., executable code/instructions) including sensor measurement software (SMSW) 32, communications software (CMSW) 34, and notification presentation software (NPSW) 36. In some embodiments, the application software 30 may include additional software that implements some or all of the processing functionality of a micromodule management system, including the tracking of statistics for the micromodules, human behavior modeling, scheduling of the micromodules, and parametrization. For purposes of brevity, the description about the application software 30 hereinafter is premised on the assumption that the various processing performed by the micromodule management system is implemented at the computing device 20, and that the presentation of the notifications based on the processing is performed at the wearable device 12 (and/or electronics device 14,
The communications software 34 comprises executable code/instructions to enable a communications circuit 38 of the wearable device 12 to operate according to one or more of a plurality of different communication technologies (e.g., NFC, Bluetooth, WiFi, including 802.11, GSM, LTE, CDMA, WCDMA, Zigbee, etc.). The communications software 34 instructs and/or controls the communications circuit 38 to transmit the raw sensor data and/or the derived information from the sensor data to the computing system 20 (e.g., directly via the cellular/wireless network 16, or indirectly via the electronics device 14). The communications software 34 may also include browser software in some embodiments to enable Internet connectivity. The communications software 34 may also be used to access certain services, such as mapping/place location services, which may be used to determine context for the sensor data. These services may be used in some embodiments of a micromodule management system, and in some instances, may not be used. In some embodiments, the communications software 34 may be external to the application software 30 or in other segments of memory. The notification presentation software 36 is configured to receive the notifications via the communications software 34 and communications circuit 38 as the notifications are communicated at different (non-overlapping) intervals based on the context (e.g., determined by the computing system 20 from the input data received from the wearable device 12). The notification presentation software 36 may format and present the notifications at an output interface 40 of the wearable device 12 at a time corresponding to when the notifications are received from the computing system 20 and/or electronics device 14 and/or at other times during the day or evening if different than when received. In some embodiments, the notification presentation software 36 may learn (e.g., based on previous notifications that were indicated, such as via feedback or use or neglect of similar and/or previous notifications) a preferred or best moment to present a current notification received from the computing system 20.
As indicated above, in one embodiment, the processing circuit 26 is coupled to the communications circuit 38. The communications circuit 38 serves to enable wireless communications between the wearable device 12 and other devices, including the electronics device 14 and the computing system 20, among other devices. The communications circuit 38 is depicted as a Bluetooth circuit, though not limited to this transceiver configuration. For instance, in some embodiments, the communications circuit 38 may be embodied as any one or a combination of an NFC circuit, WiFi circuit, transceiver circuitry based on Zigbee, 802.11, GSM, LTE, CDMA, WCDMA, among others such as optical or ultrasonic based technologies. The processing circuit 26 is further coupled to input/output (I/O) devices or peripherals, including an input interface 42 (INPUT) and the output interface 40 (OUT). Note that in some embodiments, functionality for one or more of the aforementioned circuits and/or software may be combined into fewer components/modules, or in some embodiments, further distributed among additional components/modules or devices. For instance, the processing circuit 26 may be packaged as an integrated circuit that includes the microcontroller (microcontroller unit or MCU), the DSP, and memory 28, whereas the ADC and DAC may be packaged as a separate integrated circuit coupled to the processing circuit 26. In some embodiments, one or more of the functionality for the above-listed components may be combined, such as functionality of the DSP performed by the microcontroller.
The sensors 22 are selected to perform detection and measurement of a plurality of physiological and behavioral parameters (e.g., typical behavioral parameters or activities including walking, running, cycling, and/or other activities, including shopping, walking a dog, working in the garden, etc.), including heart rate, heart rate variability, heart rate recovery, blood flow rate, activity level, muscle activity (e.g., movement of limbs, repetitive movement, core movement, body orientation/position, power, speed, acceleration, etc.), muscle tension, blood volume, blood pressure, blood oxygen saturation, respiratory rate, perspiration, skin temperature, body weight, and body composition (e.g., body mass index or BMI). At least one of the sensors 22 may be embodied as movement detecting sensors, including inertial sensors (e.g., gyroscopes, single or multi-axis accelerometers, such as those using piezoelectric, piezoresistive or capacitive technology in a microelectromechanical system (MEMS) infrastructure for sensing movement) and/or as GNSS sensors, including a GPS receiver to facilitate determinations of distance, speed, acceleration, location, altitude, etc. (e.g., location data, or generally, sensing movement), in addition to or in lieu of the accelerometer/gyroscope and/or indoor tracking (e.g., ibeacons, WiFi, coded-light based technology, etc.). The sensors 22 may also include flex and/or force sensors (e.g., using variable resistance), electromyographic sensors, electrocardiographic sensors (e.g., EKG, ECG) magnetic sensors, photoplethysmographic (PPG) sensors, bio-impedance sensors, infrared proximity sensors, acoustic/ultrasonic/audio sensors, a strain gauge, galvanic skin/sweat sensors, pH sensors, temperature sensors, pressure sensors, and photocells. The sensors 22 may include other and/or additional types of sensors for the detection of, for instance, barometric pressure, humidity, outdoor temperature, etc. In some embodiments, GNSS functionality may be achieved via the communications circuit 38 or other circuits coupled to the processing circuit 26.
The signal conditioning circuits 24 include amplifiers and filters, among other signal conditioning components, to condition the sensed signals including data corresponding to the sensed physiological parameters and/or location signals before further processing is implemented at the processing circuit 26. Though depicted in
The communications circuit 38 is managed and controlled by the processing circuit 26 (e.g., executing the communications software 34). The communications circuit 38 is used to wirelessly interface with the electronics device 14 (
In one example operation, a signal (e.g., at 2.4 GHz) may be received at the antenna and directed by the switch to the receiver circuit. The receiver circuit, in cooperation with the mixing circuit, converts the received signal into an intermediate frequency (IF) signal under frequency hopping control attributed by the frequency hopping controller and then to baseband for further processing by the ADC. On the transmitting side, the baseband signal (e.g., from the DAC of the processing circuit 26) is converted to an IF signal and then RF by the transmitter circuit operating in cooperation with the mixing circuit, with the RF signal passed through the switch and emitted from the antenna under frequency hopping control provided by the frequency hopping controller. The modulator and demodulator of the transmitter and receiver circuits may be frequency shift keying (FSK) type modulation/demodulation, though not limited to this type of modulation/demodulation, which enables the conversion between IF and baseband. In some embodiments, demodulation/modulation and/or filtering may be performed in part or in whole by the DSP. The memory 28 stores the communications software 34, which when executed by the microcontroller, controls the Bluetooth (and/or other protocols) transmission/reception.
Though the communications circuit 38 is depicted as an IF-type transceiver, in some embodiments, a direct conversion architecture may be implemented. As noted above, the communications circuit 38 may be embodied according to other and/or additional transceiver technologies.
The processing circuit 26 is depicted in
The microcontroller and the DSP provide the processing functionality for the wearable device 12. In some embodiments, functionality of both processors may be combined into a single processor, or further distributed among additional processors. The DSP provides for specialized digital signal processing, and enables an offloading of processing load from the microcontroller. The DSP may be embodied in specialized integrated circuit(s) or as field programmable gate arrays (FPGAs). In one embodiment, the DSP comprises a pipelined architecture, with comprises a central processing unit (CPU), plural circular buffers and separate program and data memories according to a Harvard architecture. The DSP further comprises dual busses, enabling concurrent instruction and data fetches. The DSP may also comprise an instruction cache and I/O controller, such as those found in Analog Devices SHARC® DSPs, though other manufacturers of DSPs may be used (e.g., Freescale multi-core MSC81xx family, Texas Instruments C6000 series, etc.). The DSP is generally utilized for math manipulations using registers and math components that may include a multiplier, arithmetic logic unit (ALU, which performs addition, subtraction, absolute value, logical operations, conversion between fixed and floating point units, etc.), and a barrel shifter. The ability of the DSP to implement fast multiply-accumulates (MACs) enables efficient execution of Fast Fourier Transforms (FFTs) and Finite Impulse Response (FIR) filtering. Some or all of the DSP functions may be performed by the microcontroller. The DSP generally serves an encoding and decoding function in the wearable device 12. For instance, encoding functionality may involve encoding commands or data corresponding to transfer of information to the electronics device 14 or a device of the computing system 20. Also, decoding functionality may involve decoding the information received from the sensors 22 (e.g., after processing by the ADC).
The microcontroller comprises a hardware device for executing software/firmware, particularly that stored in memory 28. The microcontroller can be any custom made or commercially available processor, a central processing unit (CPU), a semiconductor based microprocessor (in the form of a microchip or chip set), a macroprocessor, or generally any device for executing software instructions. Examples of suitable commercially available microprocessors include Intel's® Itanium® and Atom® microprocessors, to name a few non-limiting examples. The microcontroller provides for management and control of the wearable device 12, including determining physiological parameters or location coordinates based on the sensors 22, and for enabling communication with the electronics device 14 and/or a device of the computing system 20, and for the presentation of a chain of notifications for the micromodule management system.
The memory 28 can include any one or combination of volatile memory elements (e.g., random access memory (RAM, such as DRAM, SRAM, SDRAM, etc.)) and nonvolatile memory elements (e.g., ROM, Flash, solid state, EPROM, EEPROM, etc.). Moreover, the memory 28 may incorporate electronic, magnetic, and/or other types of storage media.
The software in memory 28 may include one or more separate programs, each of which comprises an ordered listing of executable instructions for implementing logical functions. In the example of
The operating system essentially controls the execution of other computer programs, such as the application software 30 and associated modules 32-36, and provides scheduling, input-output control, file and data management, memory management, and communication control and related services. The memory 28 may also include user data, including weight, height, age, gender, goals, body mass index (BMI) that are used by the microcontroller executing the executable code of the algorithms to accurately interpret the measured physiological and/or behavioral data. The user data may also include historical data relating past recorded data to prior contexts.
Although the application software 30 (and component parts 32-36) are described above as implemented in the wearable device 12, some embodiments may distribute the corresponding functionality among the wearable device 12 and other devices (e.g., electronics device 14 and/or one or more devices of the computing system 20), or in some embodiments, the application software 30 (and component parts 32-36) may be implemented in another device (e.g., the electronics device 14).
The software in memory 28 comprises a source program, executable program (object code), script, or any other entity comprising a set of instructions to be performed. When a source program, then the program may be translated via a compiler, assembler, interpreter, or the like, so as to operate properly in connection with the operating system. Furthermore, the software can be written as (a) an object oriented programming language, which has classes of data and methods, or (b) a procedure programming language, which has routines, subroutines, and/or functions, for example but not limited to, C, C++, Python, Java, among others. The software may be embodied in a computer program product, which may be a non-transitory computer readable medium or other medium.
The input interface 42 comprises an interface (e.g., including a user interface) for entry of user input, such as a button or microphone or sensor (e.g., to detect user input) or touch-type display. In some embodiments, the input interface 42 may serve as a communications port for downloaded information to the wearable device 12 (such as via a wired connection). The output interfaces 40 comprises an interface for the presentation or transfer of data, including a user interface (e.g., display screen presenting a graphical user interface) or communications interface for the transfer (e.g., wired) of information stored in the memory, or to enable one or more feedback devices, such as lighting devices (e.g., LEDs), audio devices (e.g., tone generator and speaker), and/or tactile feedback devices (e.g., vibratory motor). For instance, the output interface 40 may be used to present the notifications to the user. In some embodiments, at least some of the functionality of the input and output interfaces 42 and 40, respectively, may be combined, including being embodied at least in part as a touch-type display screen for the entry of input (e.g., to select an opportunity for behavioral change, such as via a presented invite in a dashboard or other screen, to input preferences, etc.) and presentation of notifications, among other data. In some embodiments, selection may be made automatically after the invitation based on detecting the context of the user (e.g., a context aware feature).
Referring now to
The smartphone 14 comprises at least two different processors, including a baseband processor (BBP) 44 and an application processor (APP) 46. As is known, the baseband processor 44 primarily handles baseband communication-related tasks and the application processor 46 generally handles inputs and outputs and all applications other than those directly related to baseband processing. The baseband processor 44 comprises a dedicated processor for deploying functionality associated with a protocol stack (PROT STK) 48, such as a GSM (Global System for Mobile communications) protocol stack, among other functions. The application processor 46 comprises a multi-core processor for running applications, including all or a portion of the application software 30A and its corresponding component parts 32A and 36A as described above in association with the wearable device 12 of
More particularly, the baseband processor 44 may deploy functionality of the protocol stack 48 to enable the smartphone 14 to access one or a plurality of wireless network technologies, including WCDMA (Wideband Code Division Multiple Access), CDMA (Code Division Multiple Access), EDGE (Enhanced Data Rates for GSM Evolution), GPRS (General Packet Radio Service), Zigbee (e.g., based on IEEE 802.15.4), Bluetooth, WiFi (Wireless Fidelity, such as based on IEEE 802.11), and/or LTE (Long Term Evolution), among variations thereof and/or other telecommunication protocols, standards, and/or specifications. The baseband processor 44 manages radio communications and control functions, including signal modulation, radio frequency shifting, and encoding. The baseband processor 44 comprises, or may be coupled to, a radio (e.g., RF front end) 54 and/or a GSM modem having one or more antennas, and analog and digital baseband circuitry (ABB, DBB, respectively in
The analog baseband circuitry is coupled to the radio 54 and provides an interface between the analog and digital domains of the GSM modem. The analog baseband circuitry comprises circuitry including an analog-to-digital converter (ADC) and digital-to-analog converter (DAC), as well as control and power management/distribution components and an audio codec to process analog and/or digital signals received indirectly via the application processor 46 or directly from the smartphone user interface 56 (e.g., microphone, earpiece, ring tone, vibrator circuits, etc.). The ADC digitizes any analog signals for processing by the digital baseband circuitry. The digital baseband circuitry deploys the functionality of one or more levels of the GSM protocol stack (e.g., Layer 1, Layer 2, etc.), and comprises a microcontroller (e.g., microcontroller unit or MCU, also referred to herein as a processor) and a digital signal processor (DSP, also referred to herein as a processor) that communicate over a shared memory interface (the memory comprising data and control information and parameters that instruct the actions to be taken on the data processed by the application processor 46). The MCU may be embodied as a RISC (reduced instruction set computer) machine that runs a real-time operating system (RTIOS), with cores having a plurality of peripherals (e.g., circuitry packaged as integrated circuits) such as RTC (real-time clock), SPI (serial peripheral interface), I2C (inter-integrated circuit), UARTs (Universal Asynchronous Receiver/Transmitter), devices based on IrDA (Infrared Data Association), SD/MMC (Secure Digital/Multimedia Cards) card controller, keypad scan controller, and USB devices, GPRS crypto module, TDMA (Time Division Multiple Access), smart card reader interface (e.g., for the one or more SIM (Subscriber Identity Module) cards), timers, and among others. For receive-side functionality, the MCU instructs the DSP to receive, for instance, in-phase/quadrature (I/Q) samples from the analog baseband circuitry and perform detection, demodulation, and decoding with reporting back to the MCU. For transmit-side functionality, the MCU presents transmittable data and auxiliary information to the DSP, which encodes the data and provides to the analog baseband circuitry (e.g., converted to analog signals by the DAC).
The application processor 46 operates under control of an operating system (OS) that enables the implementation of a plurality of user applications, including the application software 30A. The application processor 46 may be embodied as a System on a Chip (SOC), and supports a plurality of multimedia related features including web browsing to access one or more computing devices of the computing system 20 (
The device interfaces coupled to the application processor 46 may include the user interface 56, including a display screen. The display screen, similar to a display screen of the wearable device user interface, may be embodied in one of several available technologies, including LCD or Liquid Crystal Display (or variants thereof, such as Thin Film Transistor (TFT) LCD, In Plane Switching (IPS) LCD)), light-emitting diode (LED)-based technology, such as organic LED (OLED), Active-Matrix OLED (AMOLED), or retina or haptic-based technology. For instance, the display screen may be used to present web pages, dashboards, notifications, and/or other documents or data received from the computing system 20 and/or the display screen may be used to present information (e.g., notifications) in graphical user interfaces (GUIs) rendered locally in association with the application software 30A. In some embodiments, information may be presented as part of a speech communication in a spoken dialogue system. Other user interfaces 56 include a keypad, microphone, speaker, ear piece connector, I/O interfaces (e.g., USB (Universal Serial Bus)), SD/MMC card, among other peripherals. Also coupled to the application processor 46 is an image capture device (IMAGE CAPTURE) 62. The image capture device 62 comprises an optical sensor (e.g., a charged coupled device (CCD) or a complementary metal-oxide semiconductor (CMOS) optical sensor). The image capture device 62 may be used to detect various physiological parameters of a user, including blood pressure based on remote photoplethysmography (PPG). Also included is a power management device 64 that controls and manages operations of a battery 66. The components described above and/or depicted in
In the depicted embodiment, the application processor 46 runs the application software 30A, which in one embodiment, includes a plurality of software modules (e.g., executable code/instructions) including the sensor measurement software (SMSW) 32A and the notification presentation software (NPSW) 36A. Since the description of the application software 30 and software modules 32 and 36 has been described above in association with the wearable device 12 (
Referring now to
The memory 76 may store a native operating system (OS), one or more native applications, emulation systems, or emulated applications for any of a variety of operating systems and/or emulated hardware platforms, emulated operating systems, etc. In some embodiments, the processing circuit 70 may include, or be coupled to, one or more separate storage devices. For instance, in the depicted embodiment, the processing circuit 70 is coupled via the I/O interfaces 74 to template data structures (TMPDS) 82 and notification data structures (NDS) 84. In some embodiments, the template data structures 82 and/or the notifications data structures 84 may be coupled to the processing circuit 70 via the data bus 78 or coupled to the processing circuit 70 via the I/O interfaces 74 as network-connected storage devices (STOR DEVS). The data structures 82 and/or 84 may be stored in persistent memory (e.g., optical, magnetic, and/or semiconductor memory and associated drives). In some embodiments, the data structures 82 and/or 84 may be stored in memory 76.
The template data structures 82 are configured to store one or more templates that are used in a statement definition stage to generate the statements conveying information to the user. The statements for different objectives may use different templates. For example, education related statements may apply templates with referral links to educational resources, feedback on performance may apply templates with rating/ranking comments, etc. The template data structures 82 may be maintained by an administrator operating the computing system 20. The template data structures 82 may be updated based on the usage of each template, the feedback on each generated statement, etc. The templates that are more often used and/or receive more positive feedbacks from the users may be highly recommended to generate the statements in the future. In some embodiments, the templates may be general templates that can be used to generate all types of statements. In some other embodiments, the templates may be classified into categories, each category pertaining to a parameter. For example, templates for generating statement pertaining to heart rate may be partially different from templates for generating statement pertaining to sleep quality. The notifications data structures 84 are configured to store the statements that are constructed based on the templates.
In the embodiment depicted in
Referring again to
The human model component 88 comprises models of the user that are built based on available data (e.g. app usage, sensor data), available information related to preference and constraints of the users, available information for peers (e.g. same gender, race, age, lifestyle). For instance, the human model component 88 (or a data structure in coupled storage) may access user and/or peer data from data structures 96 coupled to the I/O devices 74 (directly or via network storage) or the data bus 78 (e.g., via storage device), the data structures 96 configured to store user profile data including the real-time measurements of parameters for a large population of users, personal information of the large population of users, previously generated statements related to the large population of users, etc. In some embodiments, the data structures 96 are configured to store health-related information of the user. The user profile data is organized to enable the human model component 88 to model various aspects of a user in a way that supports simple querying as well as complicated data analysis. The data structures 96 may be a backend database of the computing system 20. In some embodiments, however, the data structures 96 may be in the form of network storage and/or cloud storage directly connected to the network 18 (
The scheduling component 92 manages the micromodules over time (e.g. not more than one micromodule at the time—if at time, t, an opportunity with high score is detected and another micromodule is ongoing, the scheduling component 92 defines which priorities should be followed). This management depends on the settings of the application. For instance, if a maximum of M chains have settled at a given moment in time, and a new chain/opportunity comprises a high score, the scheduling component 92 defines the M chains to be proposed to the user at that moment in time. Note that there may be plural micromodules, each having different targets, running simultaneously. For instance, one micromodule may correspond to nutritional habits, whereas another micromodule corresponds to physical activity. The scheduling component 92 uses the data from the module history component 90 and the human model component 88 to score, over time, ongoing chains or micromodules and, eventually, new opportunities.
The parametrization component 94 adapts the proposed opportunity at time, t, based on learned parameter(s) over time from the user or peer responses to previous micromodule, which enables adjustment of a target of each micromodule. For instance, the follow-up of an opportunity (as described further in association with
The chain control logic 95 tracks the scoring of intermediate nodes in a chain, and is described further below.
The communication module formats the notifications to be issued according to one or any combination of human-perceivable format (e.g., visually, audibly, using tactile feedback, including Braille, etc.). In one embodiment, the communication module may comprise card presentation functionality. As used herein, content cards generated for a specific parameter define a “family” of statements associated with the specific parameter. For example, the content cards generated for sleep quality define a family of statements related to sleep quality, while the content cards generated for running define a family of statements related to running. The content cards may be configured to present one statement per card, though in some embodiments, additional statements may be presented. Different families may define different numbers of statements for presentation. In some embodiments, the content cards may be configured to present respective statements related to the feedback of an activity performance. In some embodiments, the content cards may be configured to present statements comprising educational information. In some embodiments, the content cards may be configured to present respective statements comprising insightful analysis of the user's health-related conditions. In some embodiments, the content cards may comprise only text statements. In some embodiments, the content cards may comprise content in multiple formats including but not limited to text, audio, video, flash, hyperlink to other sources, etc. It should be appreciated that the content cards may be generated for purposes other than the examples described above, and the format of the content cards may be adjustable for presentation on different user devices. The examples set forth above are for illustrative purposes; and the present disclosure is not intended to be limiting. For instance, presentation of the notifications is not limited to content card formats.
In one embodiment, the communications module is configured to receive the statements associated with each node and configure into content card format and present the respective content cards to the user. The communications module may prepare the presentation of the content cards based on the settings pre-defined by the user and/or the configuration of each individual user device. The settings pre-defined by the user may comprise how the user wants to be notified with the content cards, for example, in a text format, in a chart format, in an audio format with low-tone female voice, in a video/flash format, and/or the combinations thereof. The settings pre-defined by the user may further comprise when and how often the user wants to be notified with the content cards, for example, every evening around 9:00 pm, every afternoon after exercise, every week, every month, in real-time, and/or the combination thereof. The settings pre-defined by the user may further comprise a preferred user device to receive the content card if the user has multiple devices. The configuration of each individual user device may include the size and resolution of the display screen of a user device, the caching space of the user device, etc. In some embodiments, the communications module may determine the connection status of the user device before sending the content cards. If the user device is determined unavailable due to power off, offline, damaged, etc., the communications module may store the generated content card in memory 76 and/or upload the generated content card to the data structure 96. Once the user is detected logged-in using one of his or her user devices, the generated content card is transmitted to the user device for presentation. In some embodiments, if the preferred user device is unavailable, the communications module adjusts the content card for presentation in the logged-in user device.
In some embodiments, the communications module may convert a statement to one or more variations of the statement so that the converted statement matches a desired tone of voice, target population, or language, etc. The variations of a word and/or a statement may be acquired from a linguistic knowledge base. For example, the statement “Your sleep quality is highest after Mondays” may be converted to “You sleep well after Mondays.”
In some embodiments, the communications module may generate a large number of visual representations of a human body. The measurement data based on body sensors may be used to determine one or more images. The one or more images are further included in the content card or cards for presentation. Therefore, each content card presents a health picture of the individual, which can also be forwarded to a caregiver for reference. In some embodiments, the content card or cards may be presented in an orchestral arrangement of a melody played back to the user. It should be appreciated that the examples of card presentation described above are for illustrative purpose. The present disclosure is not intended to be limiting. In some embodiments, the communications module may supplement additional information to the statements for presentation of the content card. The additional information comprises professional advices on how to improve the user's health condition, feedbacks from a community environment, educational resources, etc.
The communications module further enables communications among network-connected devices and provides web and/or cloud services, among other software such as via one or more APIs. For instance, the communications module may receive (via I/O interfaces 74) input data (e.g., a content feed) from the wearable device 12 and/or the electronics device 14 that includes sensed data and a context for the sensed data, data from third-party databases (e.g., medical data base), data from social media, data from questionnaires, data from external devices (e.g., weight scales, environmental sensors, etc.), among other data. The content feed may be continual, intermittent, and/or scheduled. The communications module operates in conjunction with the I/O interfaces 74 to provide the notifications to the wearable device 12 and/or the electronics device 14.
Execution of the application software 30B (and associated components 86-94 and the communications module) may be implemented by the processor 72 under the management and/or control of the operating system. The processor 72 may be embodied as a custom-made or commercially available processor, a central processing unit (CPU) or an auxiliary processor among several processors, a semiconductor based microprocessor (in the form of a microchip), a macroprocessor, one or more application specific integrated circuits (ASICs), a plurality of suitably configured digital logic gates, and/or other well-known electrical configurations comprising discrete elements both individually and in various combinations to coordinate the overall operation of the computing system 20.
The I/O interfaces 74 comprise hardware and/or software to provide one or more interfaces to the Internet 18, as well as to other devices such as a user interface (UI) (e.g., keyboard, mouse, microphone, display screen, etc.) and/or the data structures 82,84, 96. The user interfaces may include a keyboard, mouse, microphone, immersive head set, display screen, etc., which enable input and/or output by an administrator or other user. The I/O interfaces 74 may comprise any number of interfaces for the input and output of signals (e.g., analog or digital data) for conveyance of information (e.g., data) over various networks and according to various protocols and/or standards. The user interface (UI) is configured to provide an interface between an administrator or content author and the computing system 20. The administrator may input a request via the user interface, for instance, to manage the template database 82. Upon receiving the request, the processor 72 instructs a template building component to process the request and provide information to enable the administrator to create, modify, and/or delete the templates. As indicated above, the content author may use the user interface to label statements and establish plural possible pathways among the starting, intermediate, and target nodes.
When certain embodiments of the computing system 20 are implemented at least in part with software (including firmware), as depicted in
When certain embodiments of the computing system 20 are implemented at least in part with hardware, such functionality may be implemented with any or a combination of the following technologies, which are all well-known in the art: a discrete logic circuit(s) having logic gates for implementing logic functions upon data signals, an application specific integrated circuit (ASIC) having appropriate combinational logic gates, a programmable gate array(s) (PGA), a field programmable gate array (FPGA), relays, contactors, etc.
Having described the underlying hardware and software of certain embodiments of a micromodule management system, some additional information on the formation of micromodules is described hereinafter. For instance, it is assumed, for purposes of brevity, that the statements are already constructed and hence accessed from the notifications data structures 84. In general, a statement generating component comprises algorithms that instruct a processor to generate one or more statements pertaining to a parameter. In some embodiments, the statements may be ranked for each parameter by the ranking component implementing a truth engine. In some embodiments, ranking may not be implemented. The statements are stored in the notifications data structures 84 or in other storage and accessed by a content author for use in conjunction with a chain building component. A node association component is used by the content author to associate the predetermined data structures (e.g., notifications or statements) provided by a data structure definition component (and stored in the notifications data structures 84) with either starting nodes, intermediate nodes, or target nodes.
For instance, the content author may be presented via the node association component a graphical user interface (or other interface of a software tool) that enables the content author to label the statements based on their content as start- or end-points (e.g., starting nodes and target nodes, respectively) of narratives. In one embodiment, start-point content refers to an opportunity, e.g., “On Saturdays after work you are typically less active than other evenings. Can you consider becoming more active then?”, and an end-point could be, for example, a positive observation or assessment related to a measure “Your average walking distance in Saturday evenings is 50% more than other work days. Well done! This really helps you to reach your targets earlier.” The content author further labels the statements he or she deems as appropriate as intermediate statements. The intermediate nodes comprise intermediate data structures (e.g., notifications or statements) that comprise a network of all possible intermediate statements that join the start points with the end points. Collectively, the plurality of intermediate nodes comprises a network of intermediate nodes.
A pathway establishment component is another software tool used by the content author to establish plural (e.g., all) possible pathways from the starting nodes to the target nodes (e.g., end points). A path or pathway refers to a narrative, which is a chain of statements that leads from a start-point (e.g., starting node) to an end-point (e.g., target node), collectively creating a micromodule. Using the pathway establishment component (e.g., another interactive GUI), the content author identifies all possible paths in the collection of statements, and populates a statement table for each of the starting and ending nodes based on the possible paths. In other words, each starting and ending node has a statement table that lists all possible next nodes (next statements) along with plural parameters for each statement. In one embodiment, there are typically several possible paths from a start-point to an end-point and there are also multiple paths to different end-points from one start-point. An intermediate statement in the path example introduced above could be for example, “This Saturday you have been more active than on typical Saturday evenings”. An example of different paths or pathways is illustrated in
Referring to
Referring to
The process of the chain control logic 95 terminates when the path tracking ends in one of the target nodes. The path tracking may also be terminated, for example, if the path tracking is not proceeding from one node after a predetermined threshold period (e.g., within one month). A micromodule may be identified and stored by the micromodule management system based on its context (e.g. on mornings in the weekend) and measurements that the micromodule targets to improve (e.g., walking). In one embodiment, the module history component 90 (
To conceptually illustrate example operations of an embodiment of a micromodule management system (e.g., module orchestration unit 86,
In one embodiment, the history is included in the scoring as an additional weight. The weight is based on a probability that the defined opportunity/intermediate node will lead to an end state with an achieved or overachieved goal. If more than one start node is scored higher, and the start weights based on the history include the ones represented on the left of
P[follow up|start point increase activity on Monday]=0.8
P[follow up start point increase activity on Tuesday]=0.1
Referring to
In one embodiment, the micromodule management system stores in the module history component 90 (
In view of the description above, it should be appreciated that one embodiment of a micromodule management method (e.g., implemented by the module orchestration unit 86,
Any process descriptions or blocks in the flow diagram described above should be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process, and alternate implementations are included within the scope of an embodiment of the present invention in which functions may be executed substantially concurrently, and/or additional logical functions or steps may be added, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the invention is not limited to the disclosed embodiments. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. Note that various combinations of the disclosed embodiments may be used, and hence reference to an embodiment or one embodiment is not meant to exclude features from that embodiment from use with features from other embodiments. In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. A computer program may be stored/distributed on a suitable medium, such as an optical medium or solid-state medium supplied together with or as part of other hardware, but may also be distributed in other forms.
This patent application claims the priority benefit under 35 U.S.C. § 119(e) of U.S. Provisional Application No. 62/565,395 filed on Sep. 29, 2017, the contents of which are herein incorporated by reference.
Number | Date | Country | |
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62565395 | Sep 2017 | US |