Patent Description:
Wearable articles, such as garments, incorporating sensors are wearable electronics used to measure and collect information from a wearer. Such wearable articles are commonly referred to as 'smart clothing'. It is advantageous to measure biosignals of the wearer during exercise, or other scenarios.

It is known to provide a garment, or other wearable article, to which an electronic device (i.e. an electronics module, and/or related components) is attached in a prominent position, such as on the chest or between the shoulder blades. Advantageously, the electronic device is a detachable device. The electronic device is configured to process the incoming signals, and the output from the processing is stored and/or displayed to a user in a suitable way
A sensor senses a biosignal such as electrocardiogram (ECG) signals and the biosignals are coupled to the electronic device, via an interface. The sensors may be coupled to the interface by means of conductors which are connected to terminals provided on the interface to enable coupling of the signals from the sensor to the interface.

Electronics modules for wearable articles such as garments are known to communicate with user electronic devices over wireless communication protocols such as Bluetooth ® and Bluetooth ® Low Energy. These electronics modules are typically removably attached to the wearable article, interface with internal electronics of the wearable article, and comprise a Bluetooth ® antenna for communicating with the user electronic device.

The electronic device includes drive and sensing electronics comprising components and associated circuitry, to provide the required functionality. The drive and sensing electronics include a power source to power the electronic device and the associated components of the drive and sensing circuitry.

ECG sensing is used to provide a plethora of information about a person's heart. It is one of the simplest and oldest techniques used to perform cardiac investigations. In its most basic form, it provides an insight into the electrical activity generated within heart muscles that changes over time. By detecting and amplifying these differential biopotential signals, a lot of information can be gathered quickly, including the heart rate. Among professional medical staff, individual signals have names such as "the QRS complex," which is the largest part of an ECG signal and is a collection of Q, R, and S signals, including the P and T waves.

Whilst lay persons may not be aware of the clinical aspects and significance of an ECG signal trace, lay persons would usually recognise the general form of such a signal trace, if only as a measure of heart rate.

Typically, the detected ECG signals can be displayed as a trace to a user for information. The user may be a clinician who is looking to assess cardiac health or may be a lay user using the electronics module as a fitness or health and wellness assessment device. A typical ECG waveform or trace is illustrated in <FIG> showing the QRS complex. <FIG> shows an ECG waveform of two successive heartbeats. The time difference between the two R peaks in the ECG waveform is the inter-beat interval (IBI) also known as the R-R interval. This time is usually expressed in milliseconds. IBI values represent the time between successive heartbeats.

The orthostatic heart rate (OHR) test (and other similar tests) is an established and widely used test for monitoring the fitness level of a subject. OHR test results can indicate whether the subject is stressed, overtired, overtrained, or is ill. OHR tests are widely used in the managing of training of athletes and other individuals.

An OHR test measures the difference between the resting heart rate of the subject and the orthostatic heart rate. The resting heart rate of the subject refers to the heart rate when the user is at rest such as when sitting or lying down in a relaxed position. Generally, the subject is lying down in the supine position. The orthostatic heart rate is the heart rate of the user when standing.

The difference between the resting heartrate and the orthostatic heart rate is normally around <NUM> BPM for a healthy individual. Generally, however, it is difficult for a user to determine useful information from the OHR test by itself. For example, on separate days a user may record OHR test values of <NUM>, <NUM>, <NUM> and <NUM>. It may be difficult for the user to determine the significance of these differences in scores. For example, the user may struggle to determine whether an OHR test value of <NUM> is worse than a test value of <NUM>, and the significance of having an OHR test value of <NUM> compared to an OHR test value of <NUM>.

United States Patent Application Publication No. <CIT> discloses a system, device and method of determining a probability of dehydration of a person. The method comprises receiving data of a heart rate of the person; receiving data of the posture of the person; determining that a first posture of the person satisfied first posture criteria for a first predetermined time period; determining that the posture of the person satisfies a similarity threshold with a posture envelope; determining a first heart rate for the person while in the first posture; determining a second heart rate for the person while in the second posture; determining a change in heart rate as a difference between the second heart rate and the first heart rate; determining a first probability of dehydration based at least in part on the change in heart rate; and output the first probability of dehydration.

United States Patent Application Publication No. <CIT> discloses a method for measuring stress based on the heart rate (HR) and heart rate variability (HRV), and the activity level of the user at various times during the day.

United States Patent Application Publication No. <CIT> discloses wearable electronic devices, systems and methods for sports performance monitoring.

An object of the present invention is to provide an improved method and system for determining a recovery state of a subject based on the measured heartrate values of the subject.

According to the present disclosure there is provided a computer-implemented method and system as set forth in the appended claims.

According to a first aspect of the disclosure, there is provided a computer-implemented method of calculating a recovery score for a subject. The method comprises obtaining a pair of heartrate values, a first of the values, HRrest, representing the heartrate of the subject in a resting position and a second of the values, HRstand, representing the heartrate of the subject in a standing position. The method comprises inputting the pair of heartrate values into a probability density function f(HRrest, HRstand) which uses the difference between (HRstand - HRrest) and a non-zero constant, µ, that represents a desired value of the difference between the standing and resting heart rates, to generate a recovery score for the subject. In other words, the function determines (HRstand - HRrest) - µ. The method further comprises outputting the generated recovery score.

Without being bound to any particular theory, values of HRstand - HRrest have been found to follow a generally normal distribution around an optimum value µ. The present disclosure takes advantage of this by inputting HRstand and HRrest into a probability density function so as to generate a recovery score for the subject. Thus, rather than simply outputting the value of the difference between HRstand and HRrest, the present disclosure uses HRstand and HRrest to generate a recovery score that provides an intuitive, unambiguous, indication of the recovery state of the subject.

Here, and throughout this description the "user" and the "subject" may refer to the same or different people. The user may be, for example, a medical professional, fitness instruction or coach (amongst other examples) who is monitoring the performance of the subject. Equally, the subject may be observing their own recovery score.

The function f(HRrest, HRstand) divides (HRstand - HRrest) - µ by a non-zero constant σ that defines the width of the curve of the distribution generated by the probability density function.

µ may be proportional to σ. Or equally, σ may be proportional to µ. In some examples, µ = 3σ. That is, the optimum recovery score may be equal to three standard deviations (σ). Without being bound to any particular theory, it has been found that the optimum difference between HRstand - HRrest (i.e. µ) is three standard deviations from the lowest expected difference between HRstand - HRrest and three standard deviations from the maximum expected difference between HRstand - HRrest. Thus, setting µ = 3σ is beneficial in increasing the accuracy of the generated recovery score.

σ may be determined according to the maximum expected difference between standing and resting heart rates for the subject, OHRmax. This maximum expected difference is not necessarily the same as the measured difference between HRstand - HRrest. σ may be determined according to the minimum expected difference between standing and resting heart rates for the subject, OHRmin. This minimum expected difference is not necessarily the same as the measured difference between HRstand - HRrest.

σ may be determined by calculating OHRmax - OHRmín.

σ may be determined by dividing OHRmax - OHRmin by a non-zero constant C. C may be equal to the number of standard deviations required to get from OHRmin to µ and from µ to OHRmax. In preferred examples, C = <NUM>. This follows from the finding that the optimum difference between HRstand - HRrest (i.e. µ) is three standard deviations from the lowest expected difference between HRstand - HRrest and three standard deviations from the maximum expected difference between HRstand - HRrest.

In some examples, σ = ( OHRmαx - OHRmin)/C.

OHRmax - OHRmin may be between <NUM> and <NUM>, may be between <NUM> and <NUM>, and may be equal to <NUM>. In some examples, OHRmax = <NUM> and OHRmin = <NUM>.

The values of µ, σ, OHRmax, OHRmin may be subject specific. One or more of µ, σ, OHRmax, OHRmin may be determined based on one or more characteristics of the subject. Characteristics include the subject's age, weight, gender, ethnicity, fitness level, diet, medical history, or lifestyle (e.g. whether they are a smoker). The values of µ, σ, OHRmax, OHRmin may be updated over time as characteristics of the subject change.

µ may be between <NUM> and <NUM>. µ may be between <NUM> and <NUM>. In some examples, µ is <NUM>.

The function f(HRrest,HRstand) involves determining <MAT>. The function f(HRrest, HRstand) is of the form: <MAT>.

That is, f(HRrest, HRstand)is equal to S times <MAT> times (B to the power of <MAT>).

µ is the non-zero constant that represents a desired value of the difference between the standing and resting heart rates, and acts as a location parameter that translates the peak of the curve of the distribution generated by the probability density function to a location representing an optimum recovery score for the subject.

σ is the non-zero scaling constant that defines the width of the curve of the distribution generated by the probability density function.

S is a non-zero constant that acts as a scaling factor.

In some examples, <MAT>. Here, e is the Euler number, a mathematical constant, approximately equal to <NUM>.

The constant S may scale the probability density function such the optimum values of HRstand and HRrest result in a desired maximum recovery score. In some examples, S = P × σ/A, wherein P is a non-zero constant that sets the upper limit of the recovery score. In other words, the function may be of the form: <MAT>.

Advantageously, the recovery score is unambiguous as it has defined upper and lower limits (e.g. a score of <NUM> indicates the optimum situation and a score of <NUM> indicates the worst case). The outputted recovery score can enable the user to determine, for example, whether the subject should continue to train as normal, reduce their training intensity, take a rest day or even seek medical advice.

In some examples, P = <NUM>. More generally, P is not limited to any particular value. P may be, for example, <NUM>, <NUM>, <NUM>, or <NUM>.

In some examples, the function f(HRrest, HRstand) is of the form: <MAT>.

Obtaining the pair of heartrate values may comprise:.

Calculating HRrest may comprises dividing <NUM> by the average IBI value in milliseconds for the first sequence of heartbeat data samples.

Calculating HRstand may comprise dividing <NUM> by the average IBI value in milliseconds for the second sequence of heartbeat data samples.

The method may be performed by a controller for a user electronic device. The user electronics device may further include an interface, coupled to the controller, and arranged to receive signals from an electronics module for a wearable article. The signals may comprise biosignals representing the electrical activity of the heart of the subject. The biosignals may comprise heartbeat data samples of the subject.

The method may be performed by an electronics module for a wearable article. The electronics module may have an output unit for outputting the recovery score. The output may be in the form of an audible, visual and/or haptic feedback. The electronics module may have a display for displaying the recovery score. The electronics module may be a component of a smartwatch for example.

According to a second aspect of the disclosure, there is provided a computer-readable medium having instructions recorded thereon which, when executed by a processor, cause the processor to perform the method of the first aspect of the disclosure.

According to a third aspect of the disclosure, there is provided a system for calculating a recovery score for a subject, the system comprising a processor and a memory, the memory storing instructions which when executed by the processor cause the processor to perform operations comprising:.

The function f(HRrest, HRstand) is of the form: <MAT>.

The system may further comprise a display. The display may be arranged to display the generated recovery score.

The system may comprise a user electronics device. The user electronics device may comprise the processor and the memory. The user electronics device may comprise the display and/or other form of output unit for outputting the generated recovery score. The user electronics device may comprise an interface, coupled to the controller, the controller being arranged to receive signals from an electronics module for a wearable article. The controller may be configured to obtain biosignal data for a wearer of the wearable article from the electronics module.

The system may comprise the electronics module for the wearable article. The electronics module may provide biosignal data to a user electronics device comprising the processor and the memory. The electronics module may comprise the processor and the memory. The electronics module may have an output unit for outputting the recovery score. The output may be in the form of an audible, visual and/or haptic feedback. The electronics module may have a display for displaying the recovery score. The electronics module may be a component of a smartwatch.

There is also disclosed an apparatus for calculating a recovery score for a subject, the apparatus comprising a processor and a memory, the memory storing instructions which when executed by the processor cause the processor to perform operations comprising:.

In some examples, the function f(HRrest, HRstand) divides (HRstand - HRrest) - µ by a non-zero constant σ that defines the width of the curve of the distribution generated by the probability density function.

The function f(HRrest, HRstand) may be of the form: <MAT>.

The apparatus may comprise the user electronics device of the second aspect of the disclosure or the electronics module of the second aspect of the disclosure.

The terms and words used in the following description and claims are not limited to the bibliographical meanings but are merely used by the inventor to enable a clear and consistent understanding of the disclosure.

"Wearable article" as referred to throughout the present disclosure may refer to any form of device interface which may be worn by a user such as a smart watch, necklace, garment, bracelet, or glasses. The wearable article may be a textile article. The wearable article may be a garment. The garment may refer to an item of clothing or apparel. The garment may be a top. The top may be a shirt, t-shirt, blouse, sweater, jacket/coat, or vest. The garment may be a dress, garment brassiere, shorts, pants, arm or leg sleeve, vest, jacket/coat, glove, armband, underwear, headband, hat/cap, collar, wristband, stocking, sock, or shoe, athletic clothing, personal protective equipment, including hard hats, swimwear, wetsuit or dry suit.

The term "wearer" includes a user who is wearing, or otherwise holding, the wearable article.

The type of wearable garment may dictate the type of biosignals to be detected. For example, a hat or cap may be used to detect electroencephalogram or magnetoencephalogram signals. The wearable article/garment may be constructed from a woven or a non-woven material. The wearable article/garment may be constructed from natural fibres, synthetic fibres, or a natural fibre blended with one or more other materials which can be natural or synthetic. The yarn may be cotton. The cotton may be blended with polyester and/or viscose and/or polyamide according to the application. Silk may also be used as the natural fibre. Cellulose, wool, hemp and jute are also natural fibres that may be used in the wearable article/garment. Polyester, polycotton, nylon and viscose are synthetic fibres that may be used in the wearable article/garment.

The garment may be a tight-fitting garment. Beneficially, a tight-fitting garment helps ensure that the sensor devices of the garment are held in contact with or in the proximity of a skin surface of the wearer. The garment may be a compression garment. The garment may be an athletic garment such as an elastomeric athletic garment.

The garment has sensing units provided on an inside surface which are held in close proximity to a skin surface of a wearer wearing the garment. This enables the sensing units to measure biosignals for the wearer wearing the garment.

The sensing units may be arranged to measure one or more biosignals of a wearer wearing the garment.

"Biosignal" as referred to throughout the present disclosure may refer to signals from living beings that can be continually measured or monitored. Biosignals may be electrical or non-electrical signals. Signal variations can be time variant or spatially variant.

Sensing components may be used for measuring one or a combination of bioelectrical, bioimpedance, biochemical, biomechanical, bioacoustics, biooptical or biothermal signals of the wearer <NUM>. The bioelectrical measurements include electrocardiograms (ECG), electrogastrograms (EGG), electroencephalograms (EEG), and electromyography (EMG). The bioimpedance measurements include plethysmography (e.g., for respiration), body composition (e.g., hydration, fat, etc.), and electro impedance tomography (EIT). The biomagnetic measurements include magnetoneurograms (MNG), magnetoencephalography (MEG), magnetogastrogram (MGG), magnetocardiogram (MCG). The biochemical measurements include glucose/lactose measurements which may be performed using chemical analysis of the wearer <NUM>'s sweat. The biomechanical measurements include blood pressure. The bioacoustics measurements include phonocardiograms (PCG). The biooptical measurements include orthopantomogram (OPG). The biothermal measurements include skin temperature and core body temperature measurements.

Referring to <FIG>, there is shown an example system <NUM> according to aspects of the present disclosure. The system <NUM> comprises an electronics module <NUM>, a wearable article in the form of a garment <NUM>, and a user electronic device <NUM>. The garment <NUM> is worn by a user who in this embodiment is the wearer <NUM> of the garment <NUM>.

The electronics module <NUM> is arranged to integrate with sensing units <NUM> incorporated into the garment <NUM> to obtain signals from the sensing units <NUM>.

The electronics module <NUM> and the wearable article <NUM> and including the sensing units <NUM> comprise a wearable assembly <NUM>.

The sensing units <NUM> comprise one or more sensors <NUM>, <NUM> with associated conductors <NUM>, <NUM> and other components and circuitry. The electronics module <NUM> is further arranged to wirelessly communicate data to the user electronic device <NUM>. Various protocols enable wireless communication between the electronics module <NUM> and the user electronic device <NUM>. Example communication protocols include Bluetooth ®, Bluetooth ® Low Energy, and near-field communication (NFC).

The garment <NUM> has an electronics module holder in the form of a pocket <NUM>. The pocket <NUM> is sized to receive the electronics module <NUM>. When disposed in the pocket <NUM>, the electronics module <NUM> is arranged to receive sensor data from the sensing units <NUM>. The electronics module <NUM> is therefore removable from the garment <NUM>.

The present disclosure is not limited to electronics module holders in the form pockets.

The electronics module <NUM> may be configured to be releasably mechanically coupled to the garment <NUM>. The mechanical coupling of the electronic module <NUM> to the garment <NUM> may be provided by a mechanical interface such as a clip, a plug and socket arrangement, etc. The mechanical coupling or mechanical interface may be configured to maintain the electronic module <NUM> in a particular orientation with respect to the garment <NUM> when the electronic module <NUM> is coupled to the garment <NUM>. This may be beneficial in ensuring that the electronic module <NUM> is securely held in place with respect to the garment <NUM> and/or that any electronic coupling of the electronic module <NUM> and the garment <NUM> (or a component of the garment <NUM>) can be optimized. The mechanical coupling may be maintained using friction or using a positively engaging mechanism, for example.

Beneficially, the removable electronic module <NUM> may contain all the components required for data transmission and processing such that the garment <NUM> only comprises the sensing units <NUM> e.g. the sensors <NUM>, <NUM> and communication pathways <NUM>, <NUM>. In this way, manufacture of the garment <NUM> may be simplified. In addition, it may be easier to clean a garment <NUM> which has fewer electronic components attached thereto or incorporated therein. Furthermore, the removable electronic module <NUM> may be easier to maintain and/or troubleshoot than embedded electronics. The electronic module <NUM> may comprise flexible electronics such as a flexible printed circuit (FPC).

The electronic module <NUM> may be configured to be electrically coupled to the garment <NUM>.

Referring to <FIG>, there is shown a schematic diagram of an example of the electronics module <NUM> of <FIG>. A more detailed block diagram of the electronics components of electronics module <NUM> and garment are shown in <FIG>.

The electronics module <NUM> comprises an interface <NUM>, a controller <NUM>, a power source <NUM>, and one or more communication devices which, in the exemplar embodiment comprises a first antenna <NUM>, a second antenna <NUM> and a wireless communicator <NUM>. The electronics module <NUM> also includes an input unit such as a proximity sensor or a motion sensor <NUM>, for example in the form of an inertial measurement unit (IMU).

The electronics module <NUM> also includes additional peripheral devices that are used to perform specific functions as will be described in further detail herein.

The interface <NUM> is arranged to communicatively couple with the sensing unit <NUM> of the garment <NUM>. The sensing unit <NUM> comprises - in this example - the two sensors <NUM>, <NUM> coupled to respective first and second electrically conductive pathways <NUM>, <NUM>, each with respective termination points <NUM>, <NUM>. The interface <NUM> receives signals from the sensors <NUM>, <NUM>. The controller <NUM> is communicatively coupled to the interface <NUM> and is arranged to receive the signals from the interface <NUM> for further processing.

The interface <NUM> of the embodiment described herein comprises first and second contacts <NUM>, <NUM> which are arranged to be communicatively coupled to the termination points <NUM>, <NUM> the respective first and second electrically conductive pathways <NUM>, <NUM>. The coupling between the termination points <NUM>, <NUM> and the respective first and second contacts <NUM>, <NUM> may be conductive or a wireless (e.g. inductive) communication coupling.

In this example the sensors <NUM>, <NUM> are used to measure electropotential signals such as electrocardiogram (ECG) signals, although the sensors <NUM>, <NUM> could be configured to measure other biosignal types as also discussed above.

In this embodiment, the sensors <NUM>, <NUM> are configured for so-called dry connection to the wearer's skin to measure ECG signals.

The power source <NUM> may comprise a plurality of power sources. The power source <NUM> may be a battery. The battery may be a rechargeable battery. The battery may be a rechargeable battery adapted to be charged wirelessly such as by inductive charging. The power source <NUM> may comprise an energy harvesting device. The energy harvesting device may be configured to generate electric power signals in response to kinetic events such as kinetic events <NUM> performed by the wearer <NUM> of the garment <NUM>. The kinetic event could include walking, running, exercising or respiration of the wearer <NUM>. The energy harvesting material may comprise a piezoelectric material which generates electricity in response to mechanical deformation of the converter. The energy harvesting device may harvest energy from body heat of the wearer <NUM> of the garment. The energy harvesting device may be a thermoelectric energy harvesting device. The power source <NUM> may be a super capacitor, or an energy cell.

The first antenna <NUM> is arranged to communicatively couple with the user electronic device <NUM> using a first communication protocol. In the example described herein, the first antenna <NUM> is a passive or active tag such as a passive or active Radio Frequency Identification (RFID) tag or Near Field Communication (NFC) tag. These tags comprise a communication module as well as a memory which stores the information, and a radio chip. The user electronic device <NUM> is powered to induce a magnetic field in an antenna of the user electronic device <NUM>. When the user electronic device <NUM> is placed in the magnetic field of the communication module antenna <NUM>, the user electronic device <NUM> induces current in the communication module antenna <NUM>. This induced current triggers the electronics module <NUM> to retrieve the information from the memory of the tag and transmit the same back to the user electronic device <NUM>.

In an example operation, the user electronic device <NUM> is brought into proximity with the electronics module <NUM>. In response to this, the electronics module <NUM> is configured to energize the first antenna <NUM> to transmit information to the user electronic device <NUM> over the first wireless communication protocol. Beneficially, this means that the act of the user electronic device <NUM> approaching the electronics module <NUM> energizes the first antenna <NUM> to transmit the information to the user electronic device <NUM>.

The information may comprise a unique identifier for the electronics module <NUM>. The unique identifier for the electronics module <NUM> may be an address for the electronics module <NUM> such as a MAC address or Bluetooth ® address.

The information may comprise authentication information used to facilitate the pairing between the electronics module <NUM> and the user electronic device <NUM> over the second wireless communication protocol. This means that the transmitted information is used as part of an out of band (OOB) pairing process.

The information may comprise application information which may be used by the user electronic device <NUM> to start an application on the user electronic device <NUM> or configure an application running on the user electronic device <NUM>. The application may be started on the user electronic device <NUM> automatically (e.g. without wearer <NUM> input). Alternatively, the application information may cause the user electronic device <NUM> to prompt the wearer <NUM> to start the application on the user electronic device. The information may comprise a uniform resource identifier such as a uniform resource location to be accessed by the user electronic device, or text to be displayed on the user electronic device for example. It will be appreciated that the same electronics module <NUM> can transmit any of the above example information either alone or in combination. The electronics module <NUM> may transmit different types of information depending on the current operational state of the electronics module <NUM> and based on information it receives from other devices such as the user electronic device <NUM>.

The second antenna <NUM> is arranged to communicatively couple with the user electronic device <NUM> over a second wireless communication protocol. The second wireless communication protocol may be a Bluetooth ® protocol, Bluetooth ® <NUM> or a Bluetooth ® Low Energy protocol but is not limited to any particular communication protocol. In the present embodiment, the second antenna <NUM> is integrated into controller <NUM>. The second antenna <NUM> enables communication between the user electronic device <NUM> and the controller <NUM> for configuration and set up of the controller <NUM> and the peripheral devices as may be required. Configuration of the controller <NUM> and peripheral devices utilises the Bluetooth ® protocol.

The wireless communicator <NUM> may be an alternative, or in addition to, the first and second antennas107, <NUM>.

Other wireless communication protocols can also be used, such as used for communication over: a wireless wide area network (WWAN), a wireless metro area network (WMAN), a wireless local area network (WLAN), a wireless personal area network (WPAN), Bluetooth ® Low Energy, Bluetooth ® Mesh, Thread, Zigbee, IEEE <NUM>. <NUM>, Ant, a Global Navigation Satellite System (GNSS), a cellular communication network, or any other electromagnetic RF communication protocol. The cellular communication network may be a fourth generation (<NUM>) LTE, LTE Advanced (LTE-A), LTE Cat-M1, LTE Cat-M2, NB-IoT, fifth generation (<NUM>), sixth generation (<NUM>), and/or any other present or future developed cellular wireless network.

The electronics module <NUM> includes a clock unit in the form of a real time clock (RTC) <NUM> coupled to the controller <NUM> and, for example, to be used for data logging, clock building, time stamping, timers, and alarms. As an example, the RTC <NUM> is driven by a low frequency clock source or crystal operated at <NUM>.

The electronics module <NUM> also includes a location device <NUM> such as a GNSS (Global Navigation Satellite System) device which is arranged to provide location and position data for applications as required. In particular, the location device <NUM> provides geographical location data at least to a nation state level. Any device suitable for providing location, navigation or for tracking the position could be utilised. The GNSS device may include device may include Global Positioning System (GPS), BeiDou Navigation Satellite System (BDS) and the Galileo system devices.

The power source <NUM> in this example is a lithium polymer battery <NUM>. The battery <NUM> is rechargeable and charged via a USB C input <NUM> of the electronics module <NUM>. Of course, the present disclosure is not limited to recharging via USB and instead other forms of charging such as inductive of far field wireless charging are within the scope of the present disclosure. Additional battery management functionality is provided in terms of a charge controller <NUM>, battery monitor <NUM> and regulator <NUM>. These components may be provided through use of a <NUM> dedicated power management integrated circuit (PMIC).

The USB C input <NUM> is also coupled to the controller <NUM> to enable direct communication with the controller <NUM> with an external device if required.

The controller <NUM> is communicatively connected to a battery monitor <NUM> so that that the controller <NUM> may obtain information about the state of charge of the battery <NUM>.

The controller <NUM> has an internal memory <NUM> and is also communicatively connected to an external memory <NUM> which in this example is a NAND Flash memory. The memory <NUM> is used to for the storage of data when no wireless connection is available between the electronics module <NUM> and a user electronic device <NUM>. The memory <NUM> may have a storage capacity of at least 1GB and preferably at least <NUM> GB.

The electronics module <NUM> also comprises a temperature sensor <NUM> and a light emitting diode <NUM> for conveying status information. The electronic module <NUM> also comprises conventional electronics components including a power-on-reset generator <NUM>, a development connector <NUM>, the real time clock <NUM> and a PROG header <NUM>.

Additionally, the electronics module <NUM> may comprise a haptic feedback unit <NUM> for providing a haptic (vibrational) feedback to the wearer <NUM>.

The wireless communicator <NUM> may provide wireless communication capabilities for the garment <NUM> and enables the garment to communicate via one or more wireless communication protocols to a remote server <NUM>. Wireless communications may include : a wireless wide area network (WWAN), a wireless metro area network (WMAN), a wireless local area network (WLAN), a wireless personal area network (WPAN), Bluetooth ® Low Energy, Bluetooth ® Mesh, Bluetooth ® <NUM>, Thread, Zigbee, IEEE <NUM>. <NUM>, Ant, a near field communication (NFC), a Global Navigation Satellite System (GNSS), a cellular communication network, or any other electromagnetic RF communication protocol. The cellular communication network may be a fourth generation (<NUM>) LTE, LTE Advanced (LTE-A), LTE Cat-M1, LTE Cat-M2, NB-IoT, fifth generation (<NUM>), sixth generation (<NUM>), and/or any other present or future developed cellular wireless network.

The electronics module <NUM> may additionally comprise a Universal Integrated Circuit Card (UICC) that enables the garment to access services provided by a mobile network operator (MNO) or virtual mobile network operator (VMNO). The UICC may include at least a read-only memory (ROM) configured to store an MNO or VMNO profile that the garment can utilize to register and interact with an MNO or VMNO. The UICC may be in the form of a Subscriber Identity Module (SIM) card. The electronics module <NUM> may have a receiving section arranged to receive the SIM card. In other examples, the UICC is embedded directly into a controller of the electronics module <NUM>. That is, the UICC may be an electronic/embedded UICC (eUICC). A eUICC is beneficial as it removes the need to store a number of MNO profiles, i.e. electronic Subscriber Identity Modules (eSIMs). Moreover, eSIMs can be remotely provisioned to garments. The electronics module <NUM> may comprise a secure element that represents an <NUM> embedded Universal Integrated Circuit Card (eUICC). In the present disclosure, the electronics module may also be referred to as an electronics device or unit. These terms may be used interchangeably.

The controller <NUM> is connected to the interface <NUM> via an analog-to-digital converter (ADC) front end <NUM> and an electrostatic discharge (ESD) protection circuit <NUM>.

<FIG> is a schematic illustration of the component circuitry for the ADC front end <NUM>.

In the example described herein, the ADC front end <NUM> is an integrated circuit (IC) chip which converts the raw analogue biosignal received from the sensors <NUM>, <NUM> into a digital signal for further processing by the controller <NUM>. ADC IC chips are known, and any suitable one can be utilised to provide this functionality. ADC IC chips for ECG applications include, for example, the MAX30003 chip produced by Maxim Integrated Products Inc.

The ADC front end <NUM> includes an input <NUM> and an output <NUM>.

Raw biosignals from the electrodes <NUM>, <NUM> are input to the ADC front end <NUM>, where received signals are processed in an ECG channel <NUM> and subject to appropriate filtering through high pass and low pass filters for static discharge and interference reduction as well as for reducing bandwidth prior to conversion to digital signals. The reduction in bandwidth is important to remove or reduce motion artefacts that give rise to noise in the signal due to movement of the sensors <NUM>, <NUM>.

The output digital signals may be decimated to reduce the sampling rate prior to being passed to a serial programmable interface (SPI) <NUM> of the ADC front end <NUM>.

ADC front end IC chips suitable for ECG applications may be configured to determine information from the input biosignals such as heart rate and the QRS complex and including the R-R interval. Support circuitry <NUM> provides base voltages for the ECG channel <NUM>.

The determining of the QRS complex can be implemented for example using the known Pan Tomkins algorithm as described in <NPL>.

Signals are output to the controller <NUM> via the SPI <NUM>.

The controller <NUM> can also be configured to apply digital signal processing (DSP) to the digital signal from the ADC front end <NUM>.

The DSP may include noise filtering additional to that carried out in the ADC front end <NUM> and may also include additional processing to determine further information about the signal from the ADC front end <NUM>.

The controller <NUM> is configured to send the biosignals to the user electronic device <NUM> using either of the first antenna <NUM>, second antenna <NUM>, or wireless communicator <NUM>. The biosignals sent to the user electronic device <NUM> in this example comprise the inter beat interval (IBI) values representing the time differences between successive R peaks in the measured ECG signal.

The user electronic device <NUM> in the example of <FIG> is in the form of a mobile phone or tablet and comprises a controller <NUM>, a memory <NUM>, a wireless communicator <NUM>, a display <NUM>, a user input unit <NUM>, a capturing device in the form of a camera <NUM> and an inertial measurement unit (IMU) <NUM>. The controller <NUM> provides overall control to the user electronic device <NUM>.

The user input unit <NUM> receives inputs from the user such as a user credential.

The memory <NUM> stores information for the user electronic device <NUM>.

The display <NUM> is arranged to display a user interface for applications operable on the user electronic device <NUM>.

The IMU <NUM> provides motion and/or orientation detection and may comprise an accelerometer and optionally one or both of a gyroscope and a magnetometer.

The user electronic device <NUM> may also include a biometric sensor. The biometric sensor may be used to identify a user or users of device based on unique physiological features. The biometric sensor may be: a fingerprint sensor used to capture an image of a user's fingerprint; an iris scanner or a retina scanner configured to capture an image of a user's iris or retina; an ECG module used to measure the user's ECG; or the camera of the user electronic arranged to capture the face of the user. The biometric sensor may be an internal module of the user electronic device. The biometric module may be an external (stand-alone) device which may be coupled to the user electronic device by a wired or wireless link.

The controller <NUM> is configured to launch an application which is configured to display insights derived from the biosignal data processed by the ADC front end <NUM> of the electronics module <NUM>, input to electronics module controller <NUM>, and then transmitted from the electronics module <NUM>. The transmitted data is received by the wireless communicator <NUM> of the user electronic device <NUM> and input to the controller <NUM>.

Insights include, but are not limited to, an ECG signal trace i.e. the QRS complex, heart rate, respiration rate, core temperature but can also include identification data for the wearer <NUM> using the wearable assembly <NUM>.

The display <NUM> may be a presence-sensitive display and therefore may comprise the user input unit <NUM>. The presence-sensitive display may include a display component and a presence-sensitive input component. The presence sensitive display may be a touch-screen display arranged as part of the user interface.

The user electronics device may also comprise a time of flight (TOF) sensor <NUM>.

User electronic devices in accordance with the present invention are not limited to mobile phones or tablets and may take the form of any electronic device which may be used by a user to perform the methods according to aspects of the present invention. The user electronic device <NUM> may be a electronics module such as a smartphone, tablet personal computer (PC), mobile phone, smart phone, video telephone, laptop PC, netbook computer, personal digital assistant (PDA), mobile medical device, camera or wearable device. The user electronic device <NUM> may include a head-mounted device such as an Augmented Reality, Virtual Reality or Mixed Reality head-mounted device. The user electronic device <NUM> may be desktop PC, workstations, television apparatus or a projector, e.g. arranged to project a display onto a surface.

In use, the electronics module <NUM> is configured to receive raw biosignal data from the sensors <NUM>, <NUM> and which are coupled to the controller <NUM> via the interface <NUM> and the ADC front end <NUM> for further processing and transmission to the user electronic device <NUM> as described above. The data transmitted to the user electronics device <NUM> includes raw or processed biosignal data such as ECG data, heart rate, respiration data, core temperature and other insights as determined.

The controller <NUM> of the user electronics device <NUM> is also operable to launch an application which is configured to determine and output (e.g. display) a recovery score for the subject. The user interface <NUM> displayed by the user electronics device <NUM> during the recovery score test is shown in <FIG>.

Referring to <FIG>, the recovery score application displays on the user interface <NUM> a prompt to the user to lie down, relax and breath normally. This instructs the user to adopt a resting position. The user then presses the start button <NUM> to being the measurement procedure.

After the user presses the start button <NUM>, the recovery score application transitions to the screen shown in <FIG>. The recovery score application displays an ECG waveform <NUM> using biosignal data transmitted by the electronics module <NUM> to the user electronics device <NUM>. The biosignal data received by the user electronic device <NUM> includes the recorded ECG data. The recovery score application records heartbeat data while the user is in the resting position for three minutes (other time ranges are possible) and thus obtains a first sequence of heartbeat data samples of the subject while in the resting position. A timer <NUM> displays the remaining time to the user.

After the three-minute timer has elapsed, the recovery score application transitions to the screen shown in <FIG>. The user interface <NUM> displays a prompt <NUM> to the user to stand up, relax and breathe normally. This instructs the user to adopt the standing position. In addition to a visual notification, audible and/or haptic feedback may prompt the user to adopt the standing position.

After a predetermined time interval of generally a few seconds, the recovery score application transitions to the screen in <FIG>. The recovery score application displays an ECG waveform <NUM> using biosignal data transmitted by the electronics module <NUM> to the user electronics device <NUM>. The biosignal data received by the user electronic device <NUM> includes the recorded ECG data. The recovery score application records heartbeat data while the user is in the standing position for three minutes (other time ranges are possible) obtain a second sequence of heartbeat data samples of the subject while in the standing position. A timer <NUM> displays the remaining time to the user.

Generally, the first and second sequence of heartbeat data samples comprise inter beat interval (IBI) values that are extracted from the ECG signals. That is, the user electronics device <NUM> receives the extracted IBI values from the electronics module <NUM>. In other examples, the user electronics device <NUM> may extract the IBI values from the received ECG signals.

After the timer has elapsed and the three minutes of heartbeat data has been obtained while the subject is in the standing position, the recovery score application calculates a recovery score for the subject.

In particular, the resting heart rate HRrest is calculated from the first sequence of heartbeat data samples. This involves calculating the average (e.g. mean) IBI value in milliseconds for the first sequence of heartbeat data samples and dividing <NUM> by the average IBI value.

Further, the standing heartrate HRstand is calculated from the second sequence of heartbeat data samples. This involves calculating the average (e.g. mean) IBI value in milliseconds for the second sequence of heartbeat data samples and by dividing <NUM> by the average IBI values.

Not all of the recorded heartbeat data samples may be used in calculating the resting and standing heartrates. For example, the first one minute of heartbeat data samples recorded when the user is standing may be disregarded.

The resting and standing heart rates are then input into a probability density function which generates, as an output, a recovery score for the subject. The recovery score provides a value between <NUM> (indicating a very low recovery score) and a maximum value (e.g. <NUM>) indicating an optimum recovery score.

The probability density function used by the recovery score application is of the form: <MAT>.

Preferably, the probability density function is scaled such that the probability density function outputs a score between <NUM> and a pre-defined, and preferably intuitive, maximum value (e.g. <NUM>). In these examples, S acts as a scaling constant to set the maximum value of the function.

If the desired maximum value = <NUM> then S can be determined as being equal to: <MAT>.

The score does not have to be between <NUM> and <NUM>. The score may be between any values as desired by the skilled person and which can be determined by appropriately selecting the value of the scaling constant S. That is, S may be an integer which sets the maximum desired value for the recovery score.

More generally, S may be set such = P × σ/A. P is a non-zero constant that sets the upper limit of the recovery score. In some examples, P = <NUM>. P is not limited to any particular value. P may be, for example, <NUM>, <NUM>, <NUM>, or <NUM>.

In some examples, S may equal <NUM> such that the probability density function is not scaled.

B is a non-zero constant. In some examples, <MAT>.

µ is a non-zero constant that represents a desired value of the difference between the standing and resting heart rates. µ is a location parameter that determines the location of the peak of the normal distribution. The peak of the normal distribution is the optimum difference between the standing and resting heart rates for the subject which represents the optimum recovery score. That is, µ translates the peak of the curve of the distribution generated by the probability density function to a location representing an optimum recovery score for the subject.

σ is a non-zero scaling constant that defines the width of the curve of the distribution generated by the probability density function; and
In preferred examples, µ is set to be proportional to the standard deviation. In particular, preferred examples, µ = <NUM>σ. This centres the peak of the distribution at a position that is <NUM> standard deviations from a minimum expected difference between the standing and resting heart rates for the subject, and also <NUM> standard deviations away from a maximum expected difference between the standing and resting heart rates for the subject.

In preferred examples, σ is determined according to the maximum expected difference between standing and resting heart rates for the subject, OHRmαx, and the minimum expected difference between standing and resting heart rates for the subject, OHRmin. Here, OHRmax = HRstand,max - HRrest,min. Here, OHRmin = HRstand,min - HRrest,max.

In particular, preferred examples σ is determined by calculating (OHRmax - OHRmin)/ C , where C is a non-zero constant that represents the number of standard deviations required to get from OHRmin to µ and from µ to OHRmax. C is a number greater than <NUM>. Preferably, C = <NUM>.

The present disclosure is not limited to any particular value of σ. This value is generally subject specific. σ may be between <NUM> and <NUM>, preferably between <NUM> and <NUM>, preferably still between <NUM> and <NUM>, preferably still between <NUM> and <NUM>, preferably still between <NUM> and <NUM>, preferably still between <NUM> and <NUM>. In most preferred example σ = <NUM>.

The present disclosure is not limited to any particular value of OHRmax and OHRmin. These values are generally subject specific. However, in some examples, the difference between OHRmax and OHRmin is between <NUM> and <NUM>, preferably still between <NUM> and <NUM>, and preferably still is <NUM>. In one example, OHRmax = <NUM> and OHRmín = <NUM>.

The present disclosure is not limited to any particular value of µ. The value of µ is proportional to the value of σ and so will vary as σ varies. In some examples, µ is between <NUM> and <NUM>. µ is between <NUM> and <NUM>. µ is <NUM>.

In preferred examples, the function f(HRrest, HRstand) is of the form: <MAT>.

In preferred examples, the function f(HRrest, HRstand) is of the form: <MAT> In this example, <MAT> and <MAT>.

In preferred examples still, σ = <NUM>, OHRmαx = <NUM>, OHRmin = <NUM>, µ = <NUM>. That is: <MAT>.

The generated recovery score is displayed to the user as shown in <FIG>. In particular a numerical value <NUM> between <NUM> and <NUM> is displayed to the user to indicate the recovery score. In addition, a text box <NUM> is displayed which gives a recommendation to the user based on their recovery score and potentially other factors such as hear rate variability, mental stress and physical strain. In this example, the subject has a recovery score of <NUM> out of <NUM> and is recommended to train normally.

Additional metrics are displayed to the user on the screen including the subject's orthostatic (standing) heart rate <NUM>, heart rate variability, <NUM>, mental stress score <NUM>, physical strain <NUM> and heart health score <NUM>.

In some examples, recovery score corresponds to following:.

Additional parameters may also be considered in providing recommendation to user including other factors such as the subject's heart rate variability, mental stress and physical strain. That is, a subject with a high recovery score may still be advised to reduce their training intensity based on other parameters.

<FIG> shows example normal distributions generated using the probability density function of Equation <NUM> for three different subject A, B, C. The normal distributions are generated using a fixed resting heart rate that is different for each subject and a plurality of different standing heart rates that vary over a range.

Subject A has a resting heart rate of <NUM>.

Subject B has a resting heart rate of <NUM>.

Subject C has a resting heart rate of <NUM>.

It will be appreciated that different standing heart rates will give different recovery scores for each of the users. <FIG> shows a dashed line <NUM> that represents a standing heart rate value of <NUM> and how it intersects with the normal distributions for the three different subject's A, B and C.

If subject A has a resting heart rate of <NUM> and a standing heart rate of <NUM> then they will have a recovery score of <NUM>.

If subject B has a resting heart rate of <NUM> and a standing heart rate of <NUM> then they will have a recovery score of <NUM>.

<FIG> shows a process flow diagram for an example method of calculating a recovery score according to aspects of the present disclosure.

Step S101 comprises obtaining a pair of heartrate values, a first of the values, HRrest, representing the heartrate of the subject in a resting position and a second of the values, HRstand, representing the heartrate of the subject in a standing position;
Step S102 comprises inputting the pair of heartrate values into a probability density function f(HRrest, HRstand) which generates as an output a value representing a recovery score for the subject, wherein the function f(HRrest, HRstand) is of the form shown in Equation <NUM> above.

Step S103 comprises outputting the generated recovery score.

In summary, there is provided a method and system of calculating a recovery score for a subject. The method comprises obtaining a pair of heartrate values, a first of the values, HRrest, representing the heartrate of the subject in a resting position and a second of the values, HRstand, representing the heartrate of the subject in a standing position (S101). The method further comprises inputting the pair of heartrate values into a probability density function f(HRrest, HRstand) which generates as an output a value representing a recovery score for the subject (S102). The method further comprises outputting the generated recovery score (S103).

In some embodiments, the described elements may be configured to reside on a tangible, persistent, addressable storage medium and may be configured to execute on one or more processors. These functional elements may in some embodiments include, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables.

Although the example embodiments have been described with reference to the components, modules and units discussed herein, such functional elements may be combined into fewer elements or separated into additional elements. Various combinations of optional features have been described herein, and it will be appreciated that described features may be combined in any suitable combination. In particular, the features of any one example embodiment may be combined with features of any other embodiment, as appropriate, except where such combinations are mutually exclusive. Throughout this specification, the term "comprising" or "comprises" means including the component(s) specified but not to the exclusion of the presence of others.

Claim 1:
A computer-implemented method of calculating a recovery score for a subject, the method comprising:
obtaining a pair of heartrate values, a first of the values, HRrest, representing the heartrate of the subject in a resting position and a second of the values, HRstand, representing the heartrate of the subject in a standing position (S101);
characterised in that the method further comprises:
inputting the pair of heartrate values into a probability density function f(HRrest, HRstand) which uses the difference between the value of (HRstand - HRrest) and a non-zero constant, µ, that represents a desired value of the difference between the standing and resting heart rates, to generate a recovery score for the subject (S102), wherein f(HRrest, HRstand) is of the form: <MAT>
wherein A and B are non-zero constants,
wherein µ is a non-zero constant that represents a desired value of the difference between the standing and resting heart rates, and acts as a location parameter that translates the peak of the curve of the distribution generated by the probability density function to a location representing an optimum recovery score for the subject,
wherein S is a non-zero scaling constant, and
wherein σ is a non-zero scaling constant that defines the width of the curve of the distribution generated by the probability density function; and
outputting the generated recovery score (S103).