Patent Application
20180338709
The present invention is generally related to activity tracking and, more particularly, is related to wearable devices that recognize and track activity.
A large variety of activity trackers, such as physical activity trackers, is being offered on the market. Such activity trackers may be worn as a bracelet or wristband, and include one or more sensors ranging from a single accelerometer to additional sensors such as height and/or heart rate sensors. For instance, these activity trackers may provide information relevant to fitness or health, such as steps taken during a day or distance covered. For sports activities, U.S. Pat. No. 8,353,791 describes a system containing a data logger worn by a player and sensors fitted to the players footwear, glove or a bat, stick, club, or racquet to register a kick or ball strike. Additional sensors on the data logger, such as gyro and accelerometer sensors, can be used to provide diagnostic information about a golf swing for later analysis or entertainment. For instance, the gyroscope can tell how fast the club was swung during a stroke and its appropriateness for the shot.
One object of the present invention is that a wearable device can automatically identify a type of activity.
Another object of the present invention is that a wearable device can measure one or more physiological and/or behavioral parameters based on the identified type of activity.
An embodiment of the present invention provides a wearable device that comprises a wireless receiver circuit for wirelessly receiving a local signal emanating outside of the device, the signal comprising information indicative of a type of activity selectable from among a plurality of types of activities, a plurality of sensors for sensing one or more physiological and behavioral parameters, and a processing circuit for automatically determining the type of activity based on the information in the received signal and for receiving data corresponding to the one or more physiological and behavioral parameters from one or more of the plurality of sensors based on the determination.
In an embodiment, the determined type of activity is related to a person wearing the wearable device, and the one or more physiological and/or behavioral parameters are associated with the person's body function and biomechanics (e.g., movement of all or a part of the person's body, such as a person's kicking motion or swing). Further, the one or more physiological and behavioral parameters may be used to derive additional parameters. The identification of the type of activity enables a more accurate interpretation of the person's activity and well-being. In contrast, there is a limited ability for today's activity trackers to distinguish between rudimentary types of activity. That is, walking may be distinguished from running or biking or manual input may be used after the activity during synch-up to a web-server or application for purposes of responding to predetermined questions regarding the type of activity a person is engaged in.
In an embodiment, the wireless receiver circuit for wirelessly receiving the signal coded with identifier information according to radio frequency identification technology, near field communication technology, or Bluetooth technology. The decoding of the signal enables the identification of a type of activity without requiring human intervention.
In an embodiment, the processing circuit for executing one of a plurality of selectable algorithms stored in the memory based on determining the type of activity. The fine tuning of algorithms specific to the identified type of activity enables a more accurate determination of information or parameters that are based, directly or indirectly (e.g., derived), on the data corresponding to the physiological and/or behavioral parameters, such as energy expenditure computations.
In an embodiment, further comprising an analog-to-digital converter, the processing circuit further for causing the analog-to-digital converter to operate at a higher sampling rate for data acquisition based on determining the type of activity. The ability to switch to a higher sampling rate improves the accuracy of data acquisition, and enables the wearable device to operate at lower power when an activity is not detected so as to reduce power consumption and/or the size of the power source.
In an embodiment, the processing circuit further for causing the provision of feedback responsive to determining the type of activity. Such feedback provides the person with confidence that the wearable device is operating with fidelity.
In general, certain embodiments of a wearable device are disclosed that automate the detection and determination of a type of activity, and both measure physiological and/or behavioral parameters and compute information corresponding to measured physiological and/or behavioral parameters based on the determined type of activity.
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 wearable device and corresponding method that enables automatic and reliable detection and identification of a specific type of sports activity, exercise (also referred to as fitness) activity, recreational activity (e.g., darts, billiards, etc.), household activity (e.g., painting, cleaning, etc.), social activity, and/or even sedentary activity (e.g., sleep), among other types of activities. The automating of the detection and identification process removes or mitigates the burden on a user to enter such information manually, and also increases the activity-discernment capability over fitness or activity trackers today that measure physiological parameters, such as heart rate, respiration, etc. Processing circuitry in an embodiment of a wearable device is also operatively enhanced to improve physiological and/or behavioral measurements compared to those existing in the market today through real-time use of more activity-specific algorithms and/or sensors and more robust processing.
Attention is directed to
The tags 14 may be configured as one or any combination of radio frequency identification (RFID) tags/transponders, Bluetooth transceivers, and/or near field communication (NFC) transceivers/transponders. For instance, when one or more of the tags 14 are embodied as RFID tags, the RFID tag may comprise a semiconductor (e.g., silicon) integrated circuit or microchip and one or more antennas that enable the RFID tag 14 to receive and respond to radio frequency (RF) signals transmitted by the wearable device 12. The RFID tag 14 may be of an active type (e.g., on-board or re-usable power source) or passive type (e.g., energized by radio energy provided in the signal transmitted by the wearable device 12). The RFID tag 14 further comprises memory, such as non-volatile memory, which is used to store information embodied as an identifier of the tag 14 and of an identifier of an apparatus to which the RFID tag 14 is attached. In some embodiments, the identifier may be of the type of activity (e.g., through logical association with the apparatus) for which the apparatus is normally associated. For instance, for active-type tags 14, RFID reader functionality in the wearable device 12 may generate a modulated RF signal that is communicated to the RFID tag 14. The RFID tag 14 provides a modulated RF response signal having information coded in the signal, the information corresponding to the tag identifier and the identifier of the apparatus to which the RFID tag 14 is attached and which is stored in memory of the RFID tag 14. For passive-type tags, RFID reader functionality in the wearable device 12 provides an unmodulated, continuous wave signal to activate and power the RFID tag 14, wherein in one embodiment, a back-scattered signal from the RFID tag 14 is coded with the stored identifiers. The RFID reader functionality in the wearable device 12 demodulates and decodes the information (e.g., identifiers) to automatically determine the type of apparatus (and/or the type of activity associated with the apparatus).
For tags 14 embodied as NFC tags, communication is generally achieved within 10 centimeters (cm) between the reader and tag 14 and operation is in an un-regulated (at least in some jurisdictions) RF band of 13.56 MHz. Like the RFID tags 14, the NFC tag 14 may operate in active (providing an RF field) or passive (e.g., energized by the wearable device 12) modes. It is noted that NFC is compatible with some passive-RFID infrastructures. The NFC tag 14 comprises an antenna and memory (e.g., non-volatile memory), the latter which stores information in the form of a tag identifier and identifier of the attached apparatus and/or associated activity of the attached apparatus. Communication between the tag 14 and the wearable device 12 is in the form of a modulated signal with information coded (e.g., modified Miller coding or Manchester coding) according to the stored identifiers, with active mode involving each of the wearable device 12 and tag 14 alternating their respective RF fields and in passive mode (where the tag 14 is alternatively referred to as a transponder) the field generated by the wearable device 12 modulated by the identifiers stored in the NFC tag 14. Further, in passive mode, the NFC tag 14 uses the RF field provided by the wearable device 12 to energize the tag 14.
Tags 14 embodied as Bluetooth transceivers utilize UHF radio waves (e.g., 2.4-2.485 MHz) and frequency hopping spread spectrum (e.g., dividing transmitted data into packets and transmitting each packet among seventy-nine (79) different Bluetooth channels). The tag 14 and wearable device 12 operate in a master-slave configuration, with in one embodiment, the wearable device 12 serving as the master and the tag 14 as the slave, though not limited to this configuration. The tag(s) 14 and the wearable device 12 share a common master clock embedded, in one embodiment, in the wearable device 12.
The phone 16 may be embodied as a smartphone, mobile phone, cellular phone, laptop, personal digital assistant, tablet, pager, among other handheld computing/communication devices with telephony functionality. For the sake of example, assume the phone 16 is embodied as a smartphone. The smartphone 16 comprises at least two different processors, including a baseband processor and an application processor. The baseband processor comprises a dedicated processor for deploying functionality associated with a protocol stack, such as a GSM (Global System for Mobile communications) protocol stack. The application processor comprises a multi-core processor for providing a user interface and running applications. The baseband processor and application processor have respective associated memory (e.g., random access memory (RAM), Flash memory, etc.), peripherals, and a running clock.
More particularly, the baseband processor deploys functionality of a GSM protocol stack to enable the smartphone 16 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, Wi-Fi (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 manages radio communications and control functions, including signal modulation, radio frequency shifting, and encoding. The baseband processor may comprise a GSM modem having one or more antennas, a radio (e.g., RF front end), and analog and digital baseband circuitry. The RF front end comprises a transceiver and a power amplifier to enable the receiving and transmitting of signals of a plurality of different frequencies, enabling access to the cellular network 22. The analog baseband is coupled to the radio and provides an interface between the analog and digital domains of the GSM modem. The analog baseband 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 from the smartphone user interface (e.g., microphone, earpiece, ring tone, vibrator circuits, etc.). The ADC digitizes any analog signals for processing by the digital baseband processor. The digital baseband processor 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) and a digital signal processor (DSP) 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). 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 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 (e.g., converted to analog signals by the DAC). The application processor may be embodied as a System on a Chip (SOC), and supports a plurality of multimedia related features including web browsing, email, multimedia entertainment, games, etc. The application processor includes an operating system that enables the implementation of a plurality of user applications. For instance, the application processor may deploy one or more application program interfaces (APIs) that enable access to a cloud computing framework or other networks to provide remote data access/storage/processing, and through cooperation with an embedded operating system, access to calendars, location services, reminders, etc. For instance, cloud computing may be used for storage of user data for enabling remote coaching, remote medical analysis, etc. The application processor generally comprises a processor core (Advanced RISC Machine or ARM), multimedia modules (for decoding/encoding pictures, video, and/or audio), a graphics processing unit (GPU), wireless interfaces, and device interfaces. The wireless interfaces may include a Bluetooth or Zigbee module(s) that enables wireless communication with the wearable devices 12, 20 or other local devices, a Wi-Fi module for interfacing with a local 802.11 network, and a GSM module for access to the cellular network 22 and access to the wide area network 24. The device interfaces coupled to the application processor may include a respective interface for such devices as a screen display (e.g., LCD or Liquid Crystal Display), keypad, USB (Universal Serial Bus), SD/MMC card, camera, GPRS, Wi-Fi, GPS, and/or FM radios, memory, among other devices. It should be appreciated by one having ordinary skill in the art, in the context of the present disclosure, that variations to the above may be deployed in some embodiments to achieve similar functionality.
The computer 18 may be embodied as a laptop, personal computer, workstation, tablet, among other computing devices with communication capability. The computer 18 may be in wireless or wired (e.g., temporarily, such as via USB connection, or persistently, such as an Internet connection or local area network connection) communication with other devices. The computer 18 may include similar hardware and software/firmware to that described above for the phone 16 to enable access to wireless and/or cellular networks (e.g., through communication cards comprising radio and/or cellular modem functionality) and/or other devices (e.g., Bluetooth transceivers, NFC transceivers, etc.), such as wireless or (temporary) wired connection to the wearable devices 12, 20. In some implementations, the computer 18 may be coupled to the Internet through the plain old telephone service (POTS), using technologies such as digital subscriber line (DSL), asymmetric DSL (ADSL), and/or according to broadband technology that uses a coaxial, twisted pair, and/or fiber optic medium. Discussion of such communication functionality is omitted here for brevity. Generally, in terms of hardware architecture, the computer 18 includes a processor, memory, and one or more input and/or output (I/O) devices (or peripherals) that are communicatively coupled via a local interface. The local interface can be, for example but not limited to, one or more buses or other wired or wireless connections. The local interface may have additional elements, which are omitted for brevity, such as controllers, buffers (caches), drivers, repeaters, and receivers, to enable communications. Further, the local interface may include address, control, and/or data connections to enable appropriate communications among the aforementioned components.
The processor is a hardware device for executing software, particularly that stored in memory. The processor can be any custom made or commercially available processor, a central processing unit (CPU), an auxiliary processor among several processors associated with the computer 18, a semiconductor based microprocessor (in the form of a microchip or chip set), a macroprocessor, or generally any device for executing software instructions.
The memory 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, hard drive, tape, CDROM, etc.). Moreover, the memory may incorporate electronic, magnetic, optical, semi-conductive, and/or other types of storage media. Note that the memory can have a distributed architecture, where various components are situated remote from one another, but can be accessed by the processor.
The software in memory may include one or more separate programs, each of which comprises an ordered listing of executable instructions for implementing logical functions. The software in the memory includes application software and a suitable operating system (O/S). The operating system may be embodied as a Windows operating system available from Microsoft Corporation, a Macintosh operating system available from Apple Computer, a UNIX operating system, among others. The operating system essentially controls the execution of other computer programs, and provides scheduling, input-output control, file and data management, memory management, and communication control and related services.
The I/O devices may include input devices, for example but not limited to, a keyboard, mouse, scanner, microphone, etc. Furthermore, the I/O devices may also include output devices, for example but not limited to, a printer, display, etc. Finally, the I/O devices may further include devices that communicate both inputs and outputs, for instance but not limited to, a modulator/demodulator (modem, such as to access another device, system, or network), a radio frequency (RF) or Bluetooth transceiver, a telephonic interface, a bridge, a router, etc. as indicated previously.
If the computer is a PC, workstation, or the like, the software in the memory may further include a basic input output system (BIOS). The BIOS is a set of essential software routines that initialize and test hardware at startup, start the 0/S, and support the transfer of data among the hardware devices. The BIOS is stored in ROM so that the BIOS can be executed when the computer 18 is activated.
When the computer 18 is in operation, the processor is configured to execute software stored within the memory, to communicate data to and from the memory, and to generally control operations of the computer 18 pursuant to the software.
Software can be stored on any non-transitory computer readable medium for use by or in connection with any computer related system or method. In the context of this document, a computer readable medium comprises an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device or means that can contain or store a computer program for use by or in connection with a computer related system or method. The software can be embodied in any non-transitory computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
The cellular network 22 may include the necessary infrastructure to enable cellular communications by the phone 16 and optionally the computer 18. There are a number of different digital cellular technologies suitable for use in the cellular network 22, 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 wide area network 24 may comprise one or a plurality of networks that in whole or in part comprise the Internet. Access to the Internet by the phone 16 and/or computer 18 may be enabled through one or more server devices 26 and/or networks, include PSTN (public switched telephone networks), POTS, Integrated Services digital Network (ISDN), Ethernet, Fiber, DSL/ADSL, among others.
In one example operation involving the wearable device 12, and assuming passive RFID tags 14, the wearable device 12 receives wireless signals (e.g., backscattered signals) from one or more of the passive RFID tags 14. For instance, the wearable device 12 may poll for tags 14 periodically or based on detected movements of a subject upon which the wearable device 12. The wireless signals comprise coded information such as a tag identifier and an identifier of an apparatus to which the RFID tag(s) is attached. In one embodiment, the wearable device 12 associates the identifier of the apparatus with a specific activity associated with a subject and commences heightened processing (e.g., increased sampling rate) as well as selection of a subset of available sensors for measuring physiological and/or behavioral parameters. In some embodiments, the wearable device 12 further selects an algorithm that is tailored for use in measuring physiological or behavioral parameters from the subset of sensors of the subject associated with the specific, detected activity. In some embodiments, the wearable device 12 provides feedback of the heightened processing (e.g., via a tactile alert, audible sound, tone, etc.). The wearable device 12 communicates with the phone 16 (or computer 18 in some embodiments), such as according to Bluetooth communication technology. The phone 16 may provide feedback to the subject (e.g., in the form of visual display or aural or tactile feedback) about the measured physiological and/or behavioral parameters (e.g., summary) or information related to the physiological and/or behavioral parameters, or through execution of an application and API, communicate with one or more server devices 26 coupled to the wide area network 24 (e.g., arranged in a cloud computing arrangement), enabling the data corresponding to the measured physiological or behavioral parameters to be submitted for entry in a data structure for further processing and/or synthesis with other data. For instance, the submitted data may be used for inclusion into a chart or graphic or for evaluation by a remote coach that offers consultation to a person associated with the detected activity. Note that in some embodiments, the wearable device 12 may wirelessly communicate with the phone 16 for access to a list of activity/apparatus identifiers in lieu of, or in addition to, local storage of identifiers.
Having generally described an example system 10 in which an embodiment of a wearable device 12 may be implemented, as well as an example operation involving the wearable device 12, attention is directed to
Referring first to the physiological and behavioral sensing functionality managed and coordinated by the processing circuit 32, the sensors 28 are selected to perform detection and measurement of a plurality of physiological and behavioral parameters, 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, and body composition. The sensors 28 may be embodied as 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), 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, and/or infrared proximity sensors, acoustic/ultrasonic/audio sensors, strain gauge, galvanic skin sensors/sweat, pH sensors, temperature sensors, pressure sensors, and photocells. In some embodiments, other types of sensors 28 may be used to facilitate health and/or fitness related computations, including a global navigation satellite systems (GNSS) sensor (e.g., global positioning system (GPS) sensor) to facilitate determinations of distance, speed, acceleration, location, altitude, etc., barometric pressure, humidity, outdoor temperature, etc. In some embodiments, GNSS functionality may be achieved via the external communications circuit 54. Note that in some embodiments, functionality for measuring physiological parameters may be combined using fewer sensors 28 than those listed above. Certain embodiments may use a subset of sensors 28 of the available sensors (e.g., fewer than all sensors) depending on the determined activity, and in some embodiments, the refresh rate, accuracy, or other sensor parameters may be altered depending on the detected activity.
The signal conditioning circuits 30 include amplifiers and filters, among other signal conditioning components, to condition the sensed signals including data corresponding to the sensed physiological parameters before further processing is implemented at the processing circuit 32. Though depicted in
The identifier receiving circuit 52 is managed and controlled by the processing circuit 32. In the depicted embodiment, the identifier receiving circuit 52 is embodied as an RFID reader (or interrogator) circuit for reading a passive RFID tag 14. In one embodiment, the identifier receiving circuit 52 comprises a transmitter circuit 60, a directional coupler 62, an antenna 64, a receiver circuit 66, and a signal generator circuit 68. The transmitter circuit 60 and the receiver circuit 66 comprise components suitable for providing respective transmission and reception of an RF signal, including a modulator/demodulator, filters, and amplifiers. In some embodiments, one or more of the preceding functionality may be performed by the DSP 40 or microcontroller 38. The directional coupler 62 directs energy to and from the antenna 64. The signal generator circuit 68 may be embodied as an oscillating circuit and/or frequency synthesizer, as controlled by the processing circuit 32. Control for the identifier receiving circuit 52 may be implemented by the microcontroller 38, the DSP 40, or a combination of both. In some embodiments, a separate reader controller may be implemented that is under the supervision of the microcontroller 38.
The passive RFID tag 14 is also shown in
In one example operation, and assuming the control is performed by the microcontroller 38, the microcontroller 38 issues a command (e.g., periodically, or upon prompt by the subject) to read one or more of the passive (e.g., UHF) RFID tags 14. In one embodiment, the command issued by the microcontroller 38 may include the tag identifiers of the tags 14 for which a response signal is solicited, instructions for the processor of the tag 14, and/or information to be written to the tag 14 (where read/writeable). The command may be encoded by the DSP 40, and converted to analog (e.g., via DAC 36) for use by the transmitter circuit 60 and the signal generator circuit 68. Responsively, the signal generator circuit 68 generates a radio frequency signal, and based on the radio frequency signal generated by the signal generator circuit 68, the transmitter circuit 60 provides the RF signal to the directional coupler 62. In embodiments where multiple antennas 64 are implemented, an additional switch may be used to select the appropriate antenna 64 (e.g., as directed by the microcontroller 38). The transmitter circuit 60 initially provides a non-modulated, continuous wave signal to power up the passive RFID tag 14 or tags 14 that are within range, and then provides a modulated signal (e.g., amplitude modulated) with the command encoded therein. After a defined length of time of transmission of the modulated signal, the transmitter circuit 60 provides the continuous wave signal to enable backscattering of the signal by the one or more tags 14. The backscattered signal is received at the antenna 64, and then through the directional coupler 62, which directs the received signal to the receiver circuit 66. The receiver circuit 66 demodulates the received signal and passes the signal to the ADC 34, which digitizes the signal and passes the resulting digitized signal to the DSP 40 under the direction of the microcontroller 38. The DSP 40 decodes the digitized signal and passes the decoded information to the microcontroller 38. The microcontroller 38 access the data structure 50 (e.g., look-up-table or LUT) of the processing circuit 32 to compare the decoded information to a list of identifiers (activity or apparatus identifiers) to determine a match. Based on the match, the microcontroller 38 has identified the activity associated with the RFID tag 14, and responsively causes the ADC 34 to have an elevated sampling rate and deploys the appropriate algorithms 48 and sensors 28 (e.g., subset) for processing of physiological and/or behavioral parameters of the subject engaged in the detected activity.
In some embodiments, the identifier receiving circuit 52 may deploy additional functionality, such as anti-collision functionality (e.g., tag talk first or TTF) when multiple tags 14 are under interrogation. Although described above in the context of interrogating passive RFID tags 14, it should be appreciated that similar functionality may be performed for active or semi-active RFID tags 14. For instance, active RFID tags provide their own transmitter and a power source (e.g., battery, or according to reusable energy, such as solar conversion), enabling the tags 14 to broadcast the information (tag identifier and/or apparatus identifier) to the identifier receiving circuit 52. The broadcast of the information may be prompted by a wake-up signal (e.g., continuous wave signal) from the identifier receiving circuit 52, in which case the active RFID tag 14 is referred to as a transponder. Alternatively, the broadcast of the information may be implemented via a beacon provided from the active RFID tag 14, with the beacon containing the information stored in the memory of the active RFID tag 14 (e.g., tag identifier and/or apparatus identifier) and emitted by the active RFID tag 14 at predetermined intervals (e.g., every several seconds, though longer or shorter interval durations may be used).
In some embodiments, the identifier receiving circuit 52 may be embodied as an NFC circuit. The NFC transceiver and tags have overlapping functionality, and hence have similar hardware, the discussion of which is omitted here for brevity. For instance, NFC is a subset of RFID technology, and in particular, a branch of the high frequency RFID tag (e.g., both operating at 13.56 MHz). An NFC reader and tag use inductive coupling in a similar manner to an RFID reader and tag, and use either active or passive tags (though scans of a tag in NFC are achieved one at a time). The standards and protocols of the NFC format are based on the RFID standards outlined in ISO/IEC 14443. A device configured according to NFC is also capable of being both a tag and a reader, enabling peer-to-peer communications. NFC devices can read passive NFC tags, and some NFC devices can read passive RFID tags that are compliant with ISO 15693.
It should be appreciated that two or more of the functionality for the RFID, NFC, and Bluetooth receiver may be integrated as a single package (e.g., chip) with shared componentry in some embodiments of an identifier receiving circuit, and in some embodiments, a plurality of these transceiver circuits may be deployed.
When the identifier receiving circuit 52 is embodied as a Bluetooth transceiver, the circuit illustrated in
In operation, a signal (e.g., at 2.4 GHz) may be received at the antenna 74 and directed by the switch 72 to the receiver circuit 76. The receiver circuit 76, in cooperation with the mixing circuit 78, converts the received signal into an intermediate frequency (IF) signal under frequency hopping control attributed by the frequency hopping controller 80 and then to baseband for further processing by the ADC 34. On the transmitting side, the baseband signal (e.g., from the DAC 36 of the processing circuit 32) is converted to an IF signal and then RF by the transmitter circuit 70 operating in cooperation with the mixing circuit 78, with the RF signal passed through the switch 72 and emitted from the antenna 74 under frequency hopping control provided by the frequency hopping controller 80. The modulator and demodulator of the transmitter and receiver circuits 70, 76, respectively, 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. As noted previously, in some embodiments, demodulation/modulation and/or filtering may be performed in part or in whole by the DSP 40. The memory 42 stores firmware that is executed by the microcontroller 38 to control the Bluetooth transmission/reception.
Though several examples of communication technologies have been described above for the identifier receiving circuit 52, other and/or additional technologies utilizing a tag that provides coded identifying information using acoustic, optical, among other technologies, may be used in some embodiments. Some embodiments may use vibro-tactile technologies.
Though the external communications circuit 54 is depicted as an IF-type transceiver, in some embodiments, a direct conversion architecture may be implemented. As noted above, the external communications circuit 54 may be embodied according to other and/or additional transceiver technologies, such as NFC, Wi-Fi, or Zigbee. For instance, when Zigbee and/or Wi-Fi is deployed, which can operate in the 2.4 GHz RF range, a similar physical (PHY) layer architecture may be used (e.g., with the frequency hopping controller 80 replaced with a channel selector, and possibly a different modulation/demodulation scheme, such as minimum-shift keying (MSK), among others) and a media access control (MAC) layer, application layer, and/or network layer executed by the microcontroller 38 may be configured with suitable firmware/software (e.g., communications software 49) for enabling Zigbee or Wi-Fi transmission/reception control.
The processing circuit 32 is depicted in
The microcontroller 38 and the DSP 40 provide the processing functionality for the wearable device 12. In some embodiments, functionality of both processors 38 and 40 may be combined into a single processor, or further distributed among additional processors. The DSP 40 provides for specialized digital signal processing, and enables an offloading of processing load from the microcontroller 38. The DSP 40 may be embodied in specialized integrated circuit(s) or as field programmable gate arrays (FPGAs). In one embodiment, the DSP 40 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 40 further comprises dual busses, enabling concurrent instruction and data fetches. The DSP 40 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 40 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 40 to implement fast multiply-accumulates (MACs) enables efficient execution of Fast Fourier Transforms (FFTs) and Finite Impulse Response (FIR) filtering. The DSP 40 generally serves an encoding and decoding function in the wearable device 12. For instance, encoding functionality may involve encoding commands or data corresponding to subject activity for triggering activation and operation of tags 14 and transfer of information to other electronic devices. Also, decoding functionality may involve decoding the information received from the tags 14 or from the sensors 28 (e.g., after processing by the ADC 34).
The microcontroller 38 comprises a hardware device for executing software/firmware (hereinafter, collectively, software 46 and 49), particularly that stored in memory 42. The microcontroller 38 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 38 provides for management and control of the wearable device 12, including managing the detection of activity from the tags 14, determining physiological parameters based on the sensors 28, and for enabling communication with other electronic devices.
The memory 42 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, hard drive, tape, CDROM, etc.). Moreover, the memory 42 may incorporate electronic, magnetic, and/or other types of storage media.
The software in memory 42 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 software 46, 48, and 49 comprise 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 needs to be translated via a compiler, assembler, interpreter, or the like, so as to operate properly in connection with the operating system 44. Furthermore, the software 46, 48, and 49 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 46, 48, and 49 may be embodied in a computer program product, which may be a non-transitory computer readable medium or other medium.
The input interface 56 comprises an interface for entry of user input, such as a button or microphone or sensor (e.g., to detect user input). The input interface 56 may serve as a communications port for downloaded information to the wearable device 12 (such as via a wired connection). The output interfaces 58 comprises an interface for the presentation or transfer of data, such as a display or communications interface for the transfer (e.g., wired) transfer of information stored in the memory 42, 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, a vibratory motor of the wearable device 12 may be enabled concurrently with the change in sampling rate upon detection of the activity engaged in by the subject. In some embodiments, functionality of at least some of the functionality of the input and output interfaces 56 and 58 may be combined.
In operation, the microcontroller 38 executes software 46-49 stored within the memory 42, to communicate data to and from the memory 42, and to generally control operations of the wearable device 12 pursuant to the software. For instance, responsive to determining the identity of the activity in which the subject is engaged, the microcontroller 38 instructs (e.g., directly, or via the DSP 40) the ADC 34 to change the sampling rate and, in some embodiments, signals the output interface 58 to provide feedback to the subject about the detected activity (suggesting to the subject that physiological determinations are set to begin). The microcontroller 38 uses the information about the activity to be selective as to the sensors 28 for which input is desired. For instance, if the microcontroller 38 determines that the tag 14 is attached to a pillow, then the microcontroller 38 determines that the detected activity is rest or sleep, and may signal sensors 28 corresponding to heart rate, blood pressure, etc., but may omit sensors 28 such as a GPS sensor. In other words, the microcontroller 38 may utilize only a subset of the available sensors 28 to measure the physiological and/or biological parameters. In some embodiments, accuracy and/or refresh or other parameters of the sensors 28 may be adjusted depending on the detected activity. As another example, if the detected apparatus is a golf club (e.g., where a tag 14 is affixed to the club), the microcontroller 38 determines that body movements (e.g., behavioral parameters) and physiological parameters are to be associated with the golf swing, and data from a GPS sensor 28 and possibly climate sensors 28 may be selected for processing. The microcontroller 38 further uses the information about the activity to improve the interpretation of the data, such as through selective engagement of one of the plurality of algorithms 48 based on the determined activity. For instance, rhythm (or cadence) is a factor relevant for many different sports activities (e.g., cycling, running, swimming, rowing, skating, etc.), especially in combination with breathing rate. For the detected activity, the algorithm 48 is selected as appropriate for consideration of rhythm for that activity and breathing rate determination (e.g., the optimal breathing rate and rhythm may be different for each activity, and even for sub-types of the activity, such as sprinting versus long-distance running). As another example, derived parameters such as energy expenditure (e.g., basal metabolic rate x an activity factor based on the activity-specific data) may vary depending on, among other factors, the type of activity in which the subject is engaged (e.g., lifting 100 kilograms versus 20 kilograms, rowing a boat versus swing a golf club, etc.). By selecting an activity-specific algorithm for, say, energy expenditure computations, a more accurate determination of the energy expenditure may be determined. Other types of activity-specific information include those associated with the apparatus to which the tag 14 is affixed. For instance, for racquet sports, such as tennis, the algorithms 48 executed by the microcontroller 38 may determine the total amount of times the ball has been hit during a session, the amount of high-intensity hits or hits of a specific type, and/or total distance covered. Playing tennis comprises high intensity intervals (e.g., points lasting 5-30 seconds with a few hits per rally) alternated with low intensity intervals (preparation for the next point). Arm movement and the relationship between art movements and foot steps are different for the different intervals. That is, for instance, the behavioral parameters associated with arm movements during points (e.g., balancing the racquet, keeping arms stable, swinging the racquet) are different from movements in between the rallies (e.g., walking to a starting position for the next point). Such differentiation in movement is taken into account by the microcontroller 38 and selective algorithms 48 and sensors 28 for more accurate determinations of total distance covered during a match.
Having described the underlying hardware and software of the wearable device 12, attention is now directed to
The wearable device 12, through the sensing of activity, can also automatically initiate monitoring of the swinging activity and select-physiological parameters (e.g., using select-sensors 28 and/or algorithms 48) until activity completion, providing a more accurate assessment of the activity and associated physiological and/or behavioral impact. In other words, as an example, the detection of the tag 14 causes the microcontroller 38 of the wearable device 12 to change the sampling (e.g., cause the ADC 34 to increase in sampling rate, enabling more frequent or accurate data acquisition) and further selectively switch on certain sensory functions (e.g., a subset of the sensors 28) in the wearable device 12 that are needed to accurately measure the activity. A typical example of switched on sensors specific to the activity in this example may be a PPG sensor for heart rate and possibly relative blood pressure sensing. In some embodiments, the detection of the tag 14 (the determination of the activity) activates an appropriate algorithm 48 (
Referring to
In view of the description above, it should be appreciated that one embodiment of a method for operating a wearable device, depicted in
Any process descriptions or blocks in the flow diagram of
In one embodiment, a first independent claim to a wearable device is disclosed, comprising a wireless receiver circuit for wirelessly receiving a local signal emanating outside of the wearable device, the signal comprising information indicative of a type of activity selectable from among a plurality of types of activities; a plurality of sensors for sensing one or more physiological and behavioral parameters; and a processing circuit for automatically determining the type of activity based on the information in the received signal and for receiving data corresponding to the one or more physiological and behavioral parameters from one or more of the plurality of sensors based on the determination.
The wearable device of the first independent claim, wherein the determined type of activity is related to a person wearing the wearable device, and the one or more physiological and behavioral parameters are associated with the person's body function or movement of all or a part of the person's body.
The wearable device of the first independent claim, wherein the type of activity comprises type of sports activity, type of exercise activity, type of recreational activity, type of household activity, type of social activity, or type of sedentary activity.
The wearable device of the first independent claim, wherein the wireless receiver circuit is for wirelessly receiving the signal coded with identifier information according to radio frequency identification technology, near field communication technology, or Bluetooth technology.
The wearable device of the first independent claim, the processing circuit further for activating a subset of the plurality of sensors to measure the one or more physiological and behavioral parameters based on determining the type of activity.
The wearable device of the first independent claim, further comprising memory for storing a data structure that associates the information with an apparatus or the type of activity associated with the apparatus.
The wearable device of the prior claim, the processing circuit further for executing one of a plurality of selectable algorithms stored in the memory based on determining the type of activity.
The wearable device of the prior claim, the processing circuit further for computing additional parameters based on the execution of the one of the plurality of selectable algorithms and/or the processing circuit further for distinguishing and measuring different movements associated with the determined type of activity.
The wearable device of the first independent claim, further comprising an analog-to-digital converter, the processing circuit further for causing the analog-to-digital converter to operate at a higher sampling rate for data acquisition based on determining the type of activity.
The wearable device of the first independent claim, the wireless receiver circuit further for receiving the local signal from a tag attached to an apparatus that is in direct or indirect contact with a person.
The wearable device of the first independent claim, the processing circuit further for causing the provision of feedback responsive to determining the type of activity.
The wearable device of the first independent claim, the processing circuit further for recording the one or more physiological and behavioral parameters based on the physiological and behavioral parameters meeting or exceeding a predetermined threshold level indicative of actual activity unique to the type of activity.
In one embodiment, a second independent claim to a method of operating a wearable device is disclosed, comprising: wirelessly receiving a local signal emanating outside of the wearable device, the signal comprising information indicative of a type of activity; automatically determining the type of activity based on the information in the received signal; sensing one or more physiological and behavioral parameters based on the determination; and receiving data corresponding to the one or more physiological and behavioral parameters based on the determination.
In one embodiment, a claim to a computer program product that enables a processing circuit to carry out the method of the second independent claim is disclosed.
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. For example, it is possible to operate the invention in an embodiment wherein the identification of the activity may be achieved using proximity sensing based on conductivity of the skin or body as described in U.S. Pat. No. 7,664,476 or U.S. Publication 20090124201. For instance, the tag 14 is in contact with the body (e.g., at the feet) and sends a modulated electric signal across the body, which is received by the wearable device 12 worn on the wrist. Further, though the manner of how the wearable device 12 is typically described above as worn on the wrist (e.g., as a bracelet or band), the wearable device 12 may be worn on other portions of the body directly or indirectly (e.g., through attachment to apparel worn by the person). As another example of an alternative embodiment, the wearable device 12 may make a further distinction between the type of species of apparatus among a generic type of apparatus. For instance, with golf, the swing dynamics may differ between, say, a nine-iron and a putter, and hence individual and distinctly identified tags 14 may be used for different species of apparatuses within a given genus. As another variation, although an embodiment of the wearable device 12 has been described as having memory 42 with a data structure 50 that associates the identifier information received from the tag 14 with the activity, in some embodiments, the wearable device 12 may access the memory (e.g., in the form of a SQL query or like event) of another electronic device (e.g., the phone 16, laptop 18, etc., functioning as a server in a client-server relationship to the wearable device 12) to determine the identity based on the coded identifier information (and hence not use local memory for such a data structure). The identification of an apparatus through wireless signals from a tag 14 enables additional applications beyond the use of the physiological and/or biological sensing. For instance, a tag 14 may be affixed to a cigarette lighter that, when identified by the microcontroller 38, enables the microcontroller 38 to prompt a questionnaire to help a subject understand situations and/or contexts in which the subject tends to smoke more. In some embodiments, a sensor 28 (e.g., GNSS) may be used to facilitate the context understanding. As another example, a tag 14 may be disposed in a kitchen area (e.g., affixed to a kitchen appliance), such that when in proximity to the wearable device 12 worn by the subject, triggers a questionnaire to determine the situation/context and/or requires the subject to take a weight measurement before eating. 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. Any reference signs in the claims should be not construed as limiting the scope.
This patent application claims the priority benefit under 35 U.S.C. § 119(e) of U.S. Provisional Application No. 62/261,489 filed on Dec. 1, 2015, the contents of which are herein incorporated by reference.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2016/079414 | 12/1/2016 | WO | 00 |
| Number | Date | Country | |
|---|---|---|---|
| 62261489 | Dec 2015 | US |
