EP4262544A1 - Procédé et système de génération d'un score de récupération pour un utilisateur - Google Patents

Procédé et système de génération d'un score de récupération pour un utilisateur

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Publication number
EP4262544A1
EP4262544A1 EP21830325.3A EP21830325A EP4262544A1 EP 4262544 A1 EP4262544 A1 EP 4262544A1 EP 21830325 A EP21830325 A EP 21830325A EP 4262544 A1 EP4262544 A1 EP 4262544A1
Authority
EP
European Patent Office
Prior art keywords
user
heartrate
hrv
recovery
measure
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP21830325.3A
Other languages
German (de)
English (en)
Inventor
David ROBERTAUD
Martin ASHBY
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Prevayl Innovations Ltd
Original Assignee
Prevayl Innovations Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Prevayl Innovations Ltd filed Critical Prevayl Innovations Ltd
Publication of EP4262544A1 publication Critical patent/EP4262544A1/fr
Pending legal-status Critical Current

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02405—Determining heart rate variability
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/0245—Detecting, measuring or recording pulse rate or heart rate by using sensing means generating electric signals, i.e. ECG signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1116—Determining posture transitions
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/329—Load diagnosis, e.g. cardiac stress tests
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4866—Evaluating metabolism
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4884—Other medical applications inducing physiological or psychological stress, e.g. applications for stress testing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • the present invention is directed towards a method and system for generating a recovery score for a user.
  • the present invention is directed towards methods and systems for determining a recovery score using heartrate values of the user obtained when the user is in a first position such as a resting (e.g. sitting or lying down) position and a second position such as a standing position.
  • Wearable articles such as garments, incorporating sensors are wearable electronics used to measure and collect information from a wearer.
  • wearable articles are commonly referred to as ‘smart clothing’. It is advantageous to measure biosignals of the wearer during exercise, or other scenarios.
  • an electronic device i.e. an electronics module, and/or related components
  • 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.
  • ECG electrocardiogram
  • 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.
  • 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.
  • 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 Figure 1 showing the QRS complex.
  • Figure 2 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 (I Bl) also known as the R-R interval. This time is usually expressed in milliseconds. IBI values represent the time between successive heartbeats.
  • I Bl inter-beat interval
  • IBI values represent the time between successive heartbeats.
  • OHR test (and other similar tests) is an established and widely used test for monitoring the fitness level of a user.
  • OHR test results can indicate whether the user is stressed, overtired, overtrained, or is ill.
  • OHR tests are widely used in the managing of training of athletes and other individuals.
  • the resting heart rate of the user refers to the heart rate when the user is at rest such as when sitting or lying down in a relaxed position. Generally, the user is lying down in the supine position.
  • the orthostatic heart rate is the heart rate of the user when standing.
  • the OHR test requires the user to adopt the resting position for a time period of generally 3 minutes and then transfer to the standing position for a further 3 minutes.
  • it can be challenging to ensure that the user complies with adopting these positions at the required times. It can also be challenging to ensure that the user remains in these positions during the test.
  • the heartrate data recorded while supposedly in the resting position may be inaccurate leading to an inaccurate OHR score.
  • the heartrate date recorded may be inaccurate leading to an inaccurate score.
  • Useful information includes information relating to the recovery state of the user, such as whether they are under recovered and should rest or recovered and should take part in exercise. Knowing the recovery state of the user enables the user to optimise their training schedule so as to avoid overtraining and risking injury.
  • An object of the present invention is to provide an improved method and system for performing a recovery test such as an OHR test.
  • a further object of the present invention is to provide an improved method and system for generating a recovery score from heartbeat values obtained during a recovery test such as an OHR test.
  • a computer-implemented method of performing a recovery test comprises obtaining motion data for the user.
  • the method comprises determining, from the motion data, whether the user has adopted a first position. If the user has adopted the first position, the method comprises obtaining heartbeat data for the user over a first time period; and using the heartbeat data obtained over the first time period to generate a recovery score for the user.
  • motion data is used to determine whether the user has adopted the first position before the heartbeat data is obtained over the first time period. This helps increase the accuracy of the generated recovery score and helps ensure user compliance with the recovery test without the need for human supervision.
  • the first position may be a resting position.
  • the resting position may be a position in which the user is sitting or lying down in a relaxed position. Generally, the user is lying down in the supine position
  • the method further comprises generating a prompt to the user to adopt the first position.
  • the prompt may trigger the user to adopt the first position so as to enable the heartbeat data to be obtained over the first time period. This helps ensure user compliance with the recovery test without the need for human supervision.
  • the prompt may be audible, visual or haptic prompt or may be a combination of any of audible, visual and haptic prompts.
  • the method may comprise obtaining motion data for the user during the first time period.
  • the method may comprise determining from the motion data whether the user remains in the first position.
  • the motion data can be used to ensure user compliance with the recovery test without the need for human supervision.
  • the motion data can be used to determine whether the user has deviated from the first position during the first time period. Deviating from the first position may mean that the user moves from a relaxed position such as a sitting or lying down position to a standing position. If the user has deviated from the first position then the accuracy of the recovery test will likely have been compromised as the obtained heartbeat data will not be a true reflection of the user’s heartbeat while in the first position.
  • the method may further comprises generating a prompt to the user to restart the recovery test.
  • the prompt may be audible, visual or haptic prompt or may be a combination of any of audible, visual and haptic prompts.
  • the user may be prompted to restart the recovery test if they deviate from the first position.
  • heartbeat data obtained after the user has incorrectly deviated from the first position may not be used to generate the recovery score. Instead, the recovery test may be restarted. This helps increase the accuracy of the generated recovery score.
  • the method may further comprise determining from the obtained heartbeat data whether an abnormal condition is present.
  • the abnormal condition may be a heartbeat that is too high, too low or has a high variance.
  • the present disclosure is able to identify whether the recovery test may be compromised due to abnormally recorded heartbeat data without requiring human supervision of the recovery test.
  • the method may further comprises generating a prompt to the user to restart the recovery test.
  • the method may further comprises generating a prompt to the user to seek medical advice.
  • Generating the recovery score for the user may comprise: obtaining a measure, HR first , of the heartrate of the user when in the first position; obtaining a measure, HRV first , of the heartrate variability of the user when in the first position; and generating the recovery score for the user using HR first and HRV first .
  • the method may comprise obtaining heartbeat data for the user over a second time period occurring after the first time period.
  • the method may comprise obtaining motion data for the user during the second time period.
  • the method may comprise determining from the motion data whether the user remains in a second position during the second time period.
  • the second position may be a standing position.
  • the motion data can be used to ensure user compliance with the recovery test without the need for human supervision.
  • the motion data can be used to determine whether the user has deviated from the second position during the second time period. Deviating from the second position may mean that the user moves from a standing position to a walking position or a sitting down or lying position. If the user has deviated from the second position then the accuracy of the recovery test will likely have been compromised as the obtained heartbeat data will not be a true reflection of the user’s heartbeat while in the second position.
  • the method may further comprise generating a prompt to the user to restart the recovery test.
  • the user may be prompted to restart the recovery test if they deviate from the second position.
  • heartbeat data obtained after the user has incorrectly deviated from the second position may not be used to generate the recovery score. Instead, the recovery test may be restarted. This helps increase the accuracy of the generated recovery score.
  • the method may comprise determining from the obtained heartbeat data whether an abnormal condition is present during the second time period.
  • the abnormal condition may be a heartbeat that is too high, too low or has a high variance.
  • the present disclosure is able to identify whether the recovery test has been compromised due to abnormally recorded heartbeat data without requiring human supervision of the recovery test.
  • the method may further comprise generating a prompt to the user to restart the recovery test.
  • the prompt may be audible, visual or haptic prompt or may be a combination of any of audible, visual and haptic prompts. If the abnormal condition is present, the method may further comprises generating a prompt to the user to seek medical advice.
  • the method may comprise: obtaining motion data for the user after the first time period; determining, from the motion data, whether the user has adopted the second position; and if the user has adopted the second position, the heartbeat data is obtained over the second time period.
  • motion data may be used to determine whether the user has adopted the second position before the heartbeat data is obtained over the second time period. This helps increase the accuracy of the generated recovery score and helps ensure user compliance with the recovery test without the need for human supervision.
  • the method may further comprise generating a prompt to the user to adopt the second position.
  • the prompt may trigger the user to adopt the second position so as to enable the heartbeat data to be obtained over the second time period. This helps ensure user compliance with the recovery test without the need for human supervision.
  • the method may further comprise using the heartbeat data obtained over the second time period to generate a recovery score for the user.
  • Generating the recovery score for the user may comprise: obtaining a measure, HR first , of the heartrate of the user when in the first position; obtaining a measure HR second of the heartrate of the user when in the second position; and generating the recovery score for the user using HR first and HR second .
  • Generating the recovery score may comprise using the difference between HR second and HR first .
  • Generating the recovery score for the user may comprise: obtaining a measure, HR first , of the heartrate of the userwhen in the first position; obtaining a measure, HRV first , of the heartrate variability of the user when in the first position; obtaining a measure, HR second , of the heartrate of the userwhen in a second position; and obtaining a measure, HRV second , of the heartrate variability of the user when in the second position, wherein the recovery score is generated using HR first , HRV first ,HR second , and HRV second .
  • heartrate and heartrate variability values are used to generate the recovery score rather than just heartrate values as used in existing orthostatic heart rate tests. This enhances the accuracy of the recovery score.
  • the recovery score may be generated according to a comparison of HRV first and HRV second to historic heartrate variability values of the user when in the first and second positions.
  • the present disclosure is able to determine the recovery state of the user. Generally, if the current heartrate variability values are higher than historic heartrate variability values it shows that the user is in a recovered state.
  • the recovery score may be generated according to a comparison of HR first and HR second to historic heartrate values of the user when in the first and second positions.
  • the present disclosure is able to determine the recovery state of the user. Generally, if the current heartrate values are lower than historic heartrate values it shows that the user is in a recovered state.
  • 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 the heartbeat data samples for the user and the motion data for the user.
  • 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.
  • a computer-implemented method of performing a recovery test comprising: obtaining heartbeat data for a user over a first time period; obtaining motion data for the user over the first time period; and determining, from the motion data, whether the user remains in a first position during the first time period, wherein if the user remains in the first position during the first time period, using the heartbeat data obtained over the first time period to generate a recovery score for the user.
  • the motion data can be used to ensure user compliance with the recovery test without the need for human supervision.
  • the motion data can be used to determine whether the user has deviated from the first position during the first time period. Deviating from the first position may mean that the user moves from a relaxed position such as a sitting or lying down position to a standing position. If the user has deviated from the first position then the accuracy of the recovery test will likely have been compromised as the obtained heartbeat data will not be a true reflection of the user’s heartbeat while in the first position.
  • the method may comprise any of the features of the first aspect of the disclosure.
  • a computer-readable medium having instructions recorded thereon which, when executed by a processor, cause the processor to perform the method of the first or second aspect of the disclosure.
  • a system for performing a recovery test comprising a processor and a memory, the memory storing instructions which when executed by the processor cause the processor to perform operations comprising: obtaining motion data for the user; and determining, from the motion data, whether the user has adopted a first position, wherein if the user has adopted the first position: obtaining heartbeat data for the user over a first time period; and using the heartbeat data obtained over the first time period to generate a recovery score for the user.
  • 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.
  • a computer-implemented method of generating a recovery score for a user comprises obtaining a measure, HR first , of the heartrate of the userwhen in a first position.
  • the method comprises obtaining a measure, HRV first , of the heartrate variability of the userwhen in the first position.
  • the method comprises generating a recovery score for the user using HR first and HRV first .
  • heartrate and heartrate variability values are used to generate the recovery score rather than just heartrate values as used in existing orthostatic heart rate tests. This enhances the accuracy of the recovery score.
  • the recovery score is able to take into account changes in both HR and HRV rather than just HR or HRV. Increased HRs and decreased HRVs are associated with the user being under recovered. Meanwhile decreased HRs and increased HRVs are associated with the user being recovered. There may be situations where the user’s HR is elevated and HRV is also elevated or where the user’s HR is lowered and the HRV is also lowered. Just considering HR or HRV could lead to an inaccurate estimation of the recovery state of the wearer.
  • the recovery score generated according to the present disclosure is robust against such situations and provides a more accurate reflection of the recovery state of the user.
  • the method may comprise obtaining a measure, HR second , of the heartrate of the user when in a second position.
  • the method may comprise obtaining a measure, HRV second , of the heartrate variability of the user when in the second position.
  • the recovery score may be generated using UR first , HRV first , H R second , and HRV second .
  • the first position may be a resting position.
  • the second position may be a standing position.
  • the heartrate and heartrate variability of the user when in the first and second positions are used to generate the recovery score.
  • These measures have been found to be highly correlated with the recovery state of the user and are thus beneficial in generating an accurate recovery score for the user. Therefore, using both the heartrate and heartrate variability has been found to generate a more accurate recovery score than existing approaches which consider just the heartrate in the first and second positions in isolation such as in existing orthostatic heartrate tests.
  • Heart rate variability gives a measure of how regular the heartbeat is.
  • a lower heartrate variability when compared to a previous average heartrate variability (e.g. a 2 week moving average) indicates that the user is recovered from previous exercises and otherwise has a good fitness level.
  • Obtaining HR first may comprise obtaining a first sequence of heartbeat data samples of the user when in the first position and calculating HR first from the first sequence of heartbeat data samples.
  • Calculating HR first may comprises dividing 60000 by the average IBI value in milliseconds for the first sequence of heartbeat data samples.
  • HRV first may be calculated from the first sequence of heartbeat data samples using a heartrate variability measure such as the root mean square of successive differences.
  • Obtaining HR second may comprise obtaining a second sequence of heartbeat data samples of the user when in the first position and calculating HR second from the second sequence of heartbeat data samples.
  • Calculating HR second may comprises dividing 60000 by the average IBI value in milliseconds for the second sequence of heartbeat data samples.
  • HRV second may be calculated from the second sequence of heartbeat data samples using a heartrate variability measure such as the root mean square of successive differences.
  • the recovery score may be generated according to (a) a comparison of HRV first to a historic heartrate variability value of the user when in the first position.
  • the historic heartrate variability value may be a measure of the average of the historic heart rate variability values of the user when in the first position, HRVhistoric first .
  • the recovery score may be increased if HRV first is greater than or equal to the historic heartrate variability value (e.g. HRVhistoric first ).
  • the recovery score may be generated according to (a) a comparison of HRV first and HRV second to historic heartrate variability values of the user when in the first and second positions.
  • the present disclosure is able to determine the recovery state of the user. Generally, if the current heartrate variability values are higher than historic heartrate variability values it shows that the user is in a recovered state.
  • (a) may comprise comparing HRV first and HRV second to a measure of the average of the historic heartrate variability values of the userwhen in the first position, HRVhistoric first , and a measure of the average of the historic heartrate variability values of the userwhen in the second position, HRVhistoric second .
  • (a) may comprise comparing the sum of HRV first and HRV second to the sum of HRVhistoric first and HRVhistoric second .
  • the recovery score may be increased if HRV first is greater than or equal to the historic heartrate variability value when in the first position (e.g. HRVhistoric first ).
  • the recovery score may be increased if HRV second is greater than or equal to the historic heartrate variability value when in the second position (e.g. HRVhistoric second )' .
  • the recovery score may be decreased if HRV first is less than the historic heartrate variability value when in the first position (e.g. HRVhistoric first ).
  • the recovery score may be decreased if HRV second is less than the historic heartrate variability value when in the second position (e.g. HRVhistoric second )' .
  • (a) may comprises increasing the recovery score if the sum of HRV first and HRV second is greater than or equal to the sum of HRVhistoric first and HRVhistoric second .
  • the heartrate variability for a user is reduced after periods of intense training. Therefore, by comparing current heartrate variability measures to historic heartrate variability measures for the same user, the present disclosure is able to determine whether the user is recovered or under recovered.
  • (a) may comprise decreasing the recovery score if the sum of HRV first and HRV second is less than the sum of HRVhistoric first and HRVhistoric second .
  • the recovery score may be generated according to: (b) a comparison of HR first to a historic heartrate value of the user when in the first position.
  • the historic heartrate value may be a measure of the average of the historic heartrate values of the user when in the first position, HRhistoric flrst /
  • the recovery score may be generated according to: (b) a comparison of HR first and HR second to historic heartrate values of the user when in the first and second positions.
  • the present disclosure is able to determine the recovery state of the user. Generally, if the current heartrate values are lower than historic heartrate values it shows that the user is in a recovered state.
  • (b) may comprise comparing HR first and HR second to a measure of the average of the historic heartrate values of the user when in the first position, HRhistoric first , and a measure of the average of the historic heartrate values of the user when in the second position, HRhistoric second .
  • the recovery score may be increased if HR first is less than or equal to the measure of the historic heartrate value of the user when in the first position (e.g., HRhistoric first ).
  • the recovery score may be increased if HR second is less than or equal to the measure of the historic heartrate value of the user when in the second position (e.g., HRhistoric second ).
  • the recovery score may be decreased if HR first is greater than the measure of the historic heartrate value of the user when in the first position (e.g., HRhistoric first ).
  • the recovery score may be decreased if HR second is greaterthan the measure of the historic heartrate value of the user when in the second position (e.g., HRhistoric second ).
  • (b) may comprise comparing the sum of HR first and HR second to the sum of HRhistoric first and HRhistoric second .
  • (b) may comprise increasing the recovery score if the sum of HR first and HR second is less than or equal to the sum of HRhistoriC first and HRhistoric second .
  • the heartrate for a user is increased after periods of intense training. Therefore, by comparing current heartrate measures to historic heartrate measures for the same user, the present disclosure is able to determine whether the user is recovered or under recovered.
  • (b) may comprise decreasing the recovery score if the sum of HR first and HR second is greater than the sum of HRhistoric first and HRhistoric second .
  • the recovery score may be further generated according to (c) a comparison of a measure of the difference between HR second and HR first to a threshold value.
  • (c) may comprises decreasing the recovery score if the difference between HR second and HR first is greater than a first threshold value.
  • the recovery score is decreased if the value of HR second - HR first (e.g. the orthostatic score) is too high. Having too high a difference is highly correlated with the user being under recovered.
  • (c) may comprise decreasing the recovery score if the difference between HR second and HR first is less than a second threshold value.
  • the recovery score is decreased if the value of HR second - HR first (e.g. the orthostatic score) is too low. Having too low a difference is highly correlated with the user being under recovered
  • (c) may comprise comparing the output of a probability density function f(HR first ,HR second ) to a third threshold value, wherein f(HR first ,HR second ) uses the difference between HR second and HR first and a non-zero constant, ⁇ , that represents a desired value of the difference between HR S econd and HR first to generate the output.
  • f(HR first ,HR second ) uses the difference between HR second and HR first and a non-zero constant, ⁇ , that represents a desired value of the difference between HR S econd and HR first to generate the output.
  • (c) may comprise decreasing the recovery score if the output of f(HR first ,HR second ) is less than the third threshold value. If the output of f(HR first ,HR second ) is less than the third threshold value, this indicates that the difference between HR second and HR first is outside the range of acceptable values, indicating that the user is not recovered.
  • (c) may comprise increasing the recovery score if the output of f(HR first ,HR second ) is greater than or equal to the third threshold value. If the output of f(HR first ,HR second ) is greater than or equal to the third threshold value, this indicates that the difference between HR second and HR first is within the range of acceptable values, indicating that the user is recovered.
  • the function f(HR first ,HR second ) divides (HR second - HR first ) - ⁇ by a non- zero constant ⁇ that defines the width of the curve of the distribution generated by the probability density function.
  • ⁇ may be proportional to ⁇ .
  • ⁇ may be proportional to ⁇ .
  • ⁇ 3a. That is, the optimum recovery score may be equal to three standard deviations ( ⁇ ).
  • the optimum difference between HR S econd ⁇ HRfi rst i.e. ⁇
  • the optimum difference between HR S econd ⁇ HRfi rst is three standard deviations from the lowest expected difference between HR second - HR first and three standard deviations from the maximum expected difference between HR second - HR first .
  • ⁇ 3 ⁇ is beneficial in increasing the accuracy of the generated recovery score.
  • ⁇ may be determined according to the maximum expected difference between heart rates for the user when in the first and second positions, 0HR max . This maximum expected difference is not necessarily the same as the measured difference between HR second - HR first .
  • a may be determined according to the minimum expected difference between the heart rates for the user when in the first and second positions, 0HR mln . This minimum expected difference is not necessarily the same as the measured difference between HR second - HR first .
  • a may be determined by calculating 0HR max - 0HR min .
  • ⁇ may be determined by dividing OHR max - OHR min by a non-zero constant C.
  • ⁇ ( 0HR max - 0HR mln )/C.
  • the values of ⁇ , ⁇ , 0HR max , 0HR min may be user specific. One or more of ⁇ , ⁇ , 0HR max , 0HR min may be determined based on one or more characteristics of the user. Characteristics include the user’s age, weight, gender, ethnicity, fitness level, diet, medical history, or lifestyle (e.g. whether they are a smoker). The values of ⁇ , ⁇ , 0HR max , 0HR min may be updated over time as characteristics of the user change.
  • H may be between 5 and 25.
  • ⁇ may be between 10 and 20. In some examples, ⁇ is 15.
  • the function f(HR rest ,HR stand ) may involve determining
  • the function f(HR rest ,HR stand ) may be of the form:
  • a and B are non-zero constants.
  • ⁇ is the non-zero constant that represents a desired value of the difference between the heart rates when in the first and second position, 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 user.
  • ⁇ 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.
  • e is the Euler number, a mathematical constant, approximately equal to 2.72.
  • the constant S may scale the probability density function such the optimum values of HR second and HR first result in a desired maximum recovery score.
  • S P x ⁇ /A, wherein P is a non-zero constant that sets the upper limit of the recovery score.
  • the function may be of the form:
  • P 10. More generally, P is not limited to any particular value. P may be, for example, 5, 20, 50, or 100.
  • the function f(HR first ,HR second ) is of the form:
  • the function f(HR rest ,HR stand ) is of the form:
  • the function f(HR rest ,HR stand ) is of the form:
  • the function f(HR rest ,HR stand ) is of the form:
  • the recovery score may be further generated according to: (d) a comparison of the difference between HR second and historic heartrate values of the user when in the second position to a threshold value and/or a comparison of the difference between HR first and the historic heartrate values of the user when in the first position to a threshold value.
  • (d) may comprise comparing the difference between HR second and a measure of the average of the historic heartrate values of the user when in the second position to the threshold value and/or comparing the difference between HR first and a measure of the average of the historic heartrate values of the user when in the first position to a threshold value .
  • (d) may comprise decreasing the recovery score if the difference between HR second and the measure of the average of the historic heartrate values of the user when in the second position is greater than the threshold value and/or decreasing the recovery score if the difference between HR first and the measure of the average of the historic heartrate values of the user when in the first position is greater than a threshold value .
  • a sudden change in heartrate can be a symptom of a disease or other physiological problem for the user which indicates that they are under recovered and potentially should not train or should train at a reduced intensity.
  • HR first , HRV first ,HR second , and HRV second may be determined from heartbeat data obtained during the recovery test described in relation to the first or second aspect of the disclosure.
  • 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 the heartbeat data samples for the user and the motion data for the user.
  • 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.
  • a computer-implemented method of generating a recovery score for a user comprises obtaining a measure, HR first , of the heartrate of the user when in a first position.
  • the method comprises obtaining a measure, HRV first , of the heartrate variability of the user when in the first position.
  • the method comprises obtaining a measure, HR second , of the heartrate of the userwhen in a second position.
  • the method comprises obtaining a measure, HRV second , of the heartrate variability of the user when in the second position.
  • the method comprises generating a recovery score for the user, wherein the recovery score is determined according to: a comparison of HR first and HR second to historic heartrate values of the user when in the first and second positions; and a comparison of HRV first and HRV second to historic heartrate variability values of the user when in the first and second positions.
  • the method may comprise any of the features of the fifth aspect of the disclosure.
  • a seventh 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 fifth or sixth aspect of the present disclosure.
  • a system for generating a recovery score for a user comprising a processor and a memory, the memory storing instructions which when executed by the processor cause the processor to perform operations comprising: obtaining a measure, HR first , of the heartrate of the user when in a first position; obtaining a measure, HRV first , of the heartrate variability of the user when in the first position; and generating a recovery score for the user using HR first and HRV first .
  • the operations may further comprise obtaining a measure, HR second , of the heartrate of the user when in a second position; and obtaining a measure, HRV second , of the heartrate variability of the user when in the second position.
  • the recovery score may be generated using HR first , HRV flrst , HR second , and HRV second .
  • 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.
  • the heartbeat data may be derived an ECG signal but this is not required in all examples and other signals indicative of the heartrate are within the scope of the present disclosure.
  • Other signals indicative of the heartrate include photoplethysmography (PPG) signals, ballistocardiogram (BCG) signals, and electromagnetic cardiogram (EMCG) signals.
  • PPG photoplethysmography
  • BCG ballistocardiogram
  • EMCG electromagnetic cardiogram
  • Figure 1 illustrates a signal trace for an ECG signal
  • FIG. 2 illustrates an ECG waveform that includes electrical signals for two successive heartbeats
  • Figure 3 shows a schematic diagram for an example system according to aspects of the present disclosure
  • Figure 4 shows a schematic diagram for an example electronics module according to aspects of the present disclosure
  • Figure 5 shows a schematic diagram for another example electronics module according to aspects of the present disclosure
  • Figure 6 shows a schematic diagram for an example analogue-to-digital converter used in the example electronics module of Figures 4 and 5 according to aspects of the present disclosure
  • Figure 7 shows a schematic diagram of the components of an example user electronics device according to aspects of the present disclosure
  • Figures 8 to 12 show screenshots of an example recovery score application running on a user electronics device according to aspects of the present disclosure
  • Figures 13A to 13D show a flow diagram for an example method of generating a recovery score according to aspects of the present disclosure.
  • Figure 13B is a continuation of Figure 13A.
  • Figure 13C is a continuation of Figure 13B.
  • Figure 13D is a continuation of Figure 13C;
  • Figure 14 shows a flow diagram for an example method of performing a recovery test according to aspects of the present disclosure
  • Figures 15A and 15B show a flow diagram for another example method of performing a recovery test according to aspects of the present disclosure
  • Figure 16 shows a flow diagram for another example method of performing a recovery test according to aspects of the present disclosure
  • Figure 17 shows a flow diagram for another example method of generating a recovery score according to aspects of the present disclosure.
  • Figure 18 shows a flow diagram for another example method of generating a recovery score according to aspects of the present 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.
  • 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.
  • 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 nonelectrical 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 600.
  • 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 electroimpedance tomography (EIT).
  • the biomagnetic measurements include magneto neurograms (MNG), magnetoencephalography (MEG), magnetogastrogram (MGG), magnetocardiogram (MCG).
  • the biochemical measurements include glucose/lactose measurements which may be performed using chemical analysis of the wearer 600’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.
  • the system 10 comprises an electronics module 100, a wearable article in the form of a garment 200, and a user electronic device 300.
  • the garment 200 is worn by a user who in this embodiment is the wearer 600 of the garment 200.
  • the electronics module 100 is arranged to integrate with sensing units 400 incorporated into the garment 200 to obtain signals from the sensing units 400.
  • the electronics module 100 and the wearable article 200 and including the sensing units 400 comprise a wearable assembly 500.
  • the sensing units 400 comprise one or more sensors 209, 21 1 with associated conductors 203, 207 and other components and circuitry.
  • the electronics module 100 is further arranged to wirelessly communicate data to the user electronic device 300.
  • Various protocols enable wireless communication between the electronics module 100 and the user electronic device 300.
  • Example communication protocols include Bluetooth ®, Bluetooth ® Low Energy, and near-field communication (NFC).
  • the garment 200 has an electronics module holder in the form of a pocket 201 .
  • the pocket 201 is sized to receive the electronics module 100.
  • the electronics module 100 is arranged to receive sensor data from the sensing units 400.
  • the electronics module 100 is therefore removable from the garment 200.
  • the present disclosure is not limited to electronics module holders in the form pockets.
  • the electronics module 100 may be configured to be releasably mechanically coupled to the garment 200.
  • the mechanical coupling of the electronic module 100 to the garment 200 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 100 in a particular orientation with respect to the garment 200 when the electronic module 100 is coupled to the garment 200. This may be beneficial in ensuring that the electronic module 100 is securely held in place with respect to the garment 200 and/or that any electronic coupling of the electronic module 100 and the garment 200 (or a component of the garment 200) can be optimized.
  • the mechanical coupling may be maintained using friction or using a positively engaging mechanism, for example.
  • the removable electronic module 100 may contain all the components required for data transmission and processing such that the garment 200 only comprises the sensing units 400 e.g. the sensors 209, 211 and communication pathways 203, 207. In this way, manufacture of the garment 200 may be simplified. In addition, it may be easier to clean a garment 200 which has fewer electronic components attached thereto or incorporated therein. Furthermore, the removable electronic module 100 may be easierto maintain and/ortroubleshoot than embedded electronics.
  • the electronic module 100 may comprise flexible electronics such as a flexible printed circuit (FPC).
  • the electronic module 100 may be configured to be electrically coupled to the garment 200.
  • FIG 4 there is shown a schematic diagram of an example of the electronics module 100 of Figure 1.
  • FIG 5 A more detailed block diagram of the electronics components of electronics module 100 and garment are shown in Figure 5.
  • the electronics module 100 comprises an interface 101 , a controller 103, a power source 105, and one or more communication devices which, in the exemplar embodiment comprises a first antenna 107, a second antenna 109 and a wireless communicator 159.
  • the electronics module 100 also includes an input unit such as a proximity sensor or a motion sensor 111 , for example in the form of an inertial measurement unit (IMU).
  • IMU inertial measurement unit
  • the electronics module 100 also includes additional peripheral devices that are used to perform specific functions as will be described in further detail herein.
  • the interface 101 is arranged to communicatively couple with the sensing unit 400 of the garment 200.
  • the sensing unit 400 comprises - in this example - the two sensors 209, 211 coupled to respective first and second electrically conductive pathways 203, 207, each with respective termination points 213, 215.
  • the interface 101 receives signals from the sensors 209, 211.
  • the controller 103 is communicatively coupled to the interface 101 and is arranged to receive the signals from the interface 101 for further processing.
  • the interface 101 of the embodiment described herein comprises first and second contacts 163, 165 which are arranged to be communicatively coupled to the termination points 213, 215 the respective first and second electrically conductive pathways 203, 207.
  • the coupling between the termination points 213, 215 and the respective first and second contacts 163, 165 may be conductive or a wireless (e.g. inductive) communication coupling.
  • the sensors 209, 211 are used to measure electropotential signals such as electrocardiogram (ECG) signals, although the sensors 209, 211 could be configured to measure other biosignal types as also discussed above.
  • ECG electrocardiogram
  • the sensors 209, 211 are configured for so-called dry connection to the wearer’s skin to measure ECG signals.
  • the power source 105 may comprise a plurality of power sources.
  • the power source 105 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 105 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 10 performed by the wearer 600 of the garment 200.
  • the kinetic event could include walking, running, exercising or respiration of the wearer 600.
  • 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 ofthe wearer 600 of the garment.
  • the energy harvesting device may be a thermoelectric energy harvesting device.
  • the power source 105 may be a super capacitor, or an energy cell.
  • the first antenna 107 is arranged to communicatively couple with the user electronic device 300 using a first communication protocol.
  • the first antenna 107 is a passive tag such as a passive Radio Frequency Identification (RFID) tag or Near Field Communication (NFC) tag.
  • RFID Radio Frequency Identification
  • NFC Near Field Communication
  • These tags comprise a communication module as well as a memory which stores the information, and a radio chip.
  • the user electronic device 300 is powered to induce a magnetic field in an antenna ofthe user electronic device 300.
  • the user electronic device 300 When the user electronic device 300 is placed in the magnetic field of the communication module antenna 107, the user electronic device 300 induces current in the communication module antenna 107. This induced current triggers the electronics module 100 to retrieve the information from the memory of the tag and transmit the same back to the user electronic device 300.
  • the user electronic device 300 is brought into proximity with the electronics module 100.
  • the electronics module 100 is configured to energize the first antenna 107 to transmit information to the user electronic device 300 over the first wireless communication protocol.
  • the information may comprise a unique identifier for the electronics module 100.
  • the unique identifier for the electronics module 100 may be an address for the electronics module 100 such as a MAC address or Bluetooth ® address.
  • the information may comprise authentication information used to facilitate the pairing between the electronics module 100 and the user electronic device 300 over the second wireless communication protocol. This means that the transmitted information is used as part of an out of band (OOB) pairing process.
  • OOB out of band
  • the information may comprise application information which may be used by the user electronic device 300 to start an application on the user electronic device 300 or configure an application running on the user electronic device 300.
  • the application may be started on the user electronic device 300 automatically (e.g. without wearer 600 input).
  • the application information may cause the user electronic device 300 to prompt the wearer 600 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 100 can transmit any of the above example information either alone or in combination.
  • the electronics module 100 may transmit different types of information depending on the current operational state of the electronics module 100 and based on information it receives from other devices such as the user electronic device 300.
  • the second antenna 109 is arranged to communicatively couple with the user electronic device 300 over a second wireless communication protocol.
  • the second wireless communication protocol may be a Bluetooth ® protocol, Bluetooth ® 5 or a Bluetooth ® Low Energy protocol but is not limited to any particular communication protocol.
  • the second antenna 109 is integrated into controller 103.
  • the second antenna 109 enables communication between the user electronic device 300 and the controller 100 for configuration and set up of the controller 103 and the peripheral devices as may be required. Configuration of the controller 103 and peripheral devices utilises the Bluetooth ® protocol.
  • the wireless communicator 159 may be an alternative, or in addition to, the first and second antennas107, 109.
  • 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 802.15.4, Ant, a Global Navigation Satellite System (GNSS), a cellular communication network, or any other electromagnetic RF communication protocol.
  • WWAN wireless wide area network
  • WMAN wireless metro area network
  • WLAN wireless local area network
  • WPAN wireless personal area network
  • Bluetooth ® Low Energy Bluetooth ® Mesh, Thread, Zigbee, IEEE 802.15.4, Ant, a Global Navigation Satellite System (GNSS), a cellular communication network, or any other electromagnetic RF communication protocol.
  • GNSS Global Navigation Satellite System
  • the cellular communication network may be a fourth generation (4G) LTE, LTE Advanced (LTE-A), LTE Cat-M1 , LTE Cat-M2, NB-loT, fifth generation (5G), sixth generation (6G), and/or any other present or future developed cellular wireless network.
  • 4G fourth generation
  • LTE-A LTE Advanced
  • LTE Cat-M1 LTE Cat-M2
  • NB-loT fifth generation
  • 5G fifth generation
  • 6G sixth generation
  • any other present or future developed cellular wireless network may be any other present or future developed cellular wireless network.
  • the electronics module 100 includes configured a clock unit in the form of a real time clock (RTC) 153 coupled to the controller 103 and, for example, to be used for data logging, clock building, time stamping, timers, and alarms.
  • RTC real time clock
  • the RTC 153 is driven by a low frequency clock source or crystal operated at 32.768 Hz.
  • the electronics module 100 also includes a location device 161 such as a GNSS (Global Navigation Satellite System) device which is arranged to provide location and position data for applications as required.
  • a location device 161 such as a GNSS (Global Navigation Satellite System) device which is arranged to provide location and position data for applications as required.
  • the location device 161 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 105 in this example is a lithium polymer battery 105.
  • the battery 105 is rechargeable and charged via a USB C input 131 of the electronics module 100.
  • 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 133, battery monitor 135 and regulator 147. These components may be provided through use of a 30 dedicated power management integrated circuit (PMIC).
  • PMIC power management integrated circuit
  • the USB C input 131 is also coupled to the controller 131 to enable direct communication with the controller 103 with an external device if required.
  • the controller 103 is communicatively connected to a battery monitor 135 so that that the controller 103 may obtain information about the state of charge of the battery 105.
  • the controller 103 has an internal memory 167 and is also communicatively connected to an external memory 143 which in this example is a NAND Flash memory.
  • the memory 143 is used to for the storage of data when no wireless connection is available between the electronics module 100 and a user electronic device 300.
  • the memory 143 may have a storage capacity of at least 1 GB and preferably at least 2 GB.
  • the electronics module 100 also comprises a temperature sensor 145 and a light emitting diode 147 for conveying status information.
  • the electronic module 100 also comprises conventional electronics components including a power-on-reset generator 149, a development connector 151 , the real time clock 153 and a PROG header 155.
  • the electronics module 100 may comprise a haptic feedback unit 157 for providing a haptic (vibrational) feedback to the wearer 600.
  • the wireless communicator 159 may provide wireless communication capabilities for the garment 200 and enables the garment to communicate via one or more wireless communication protocols to a remote server 700.
  • 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 ® 5, Thread, Zigbee, IEEE 802.15.4, Ant, a near field communication (NFC), a Global Navigation Satellite System (GNSS), a cellular communication network, or any other electromagnetic RF communication protocol.
  • WWAN wireless wide area network
  • WMAN wireless metro area network
  • WLAN wireless local area network
  • WPAN wireless personal area network
  • Bluetooth ® Low Energy Bluetooth ® Mesh
  • Bluetooth ® 5 Thread
  • Zigbee IEEE 802.15.4
  • Ant Ant
  • NFC near field communication
  • GNSS Global Navigation Satellite System
  • cellular communication network or any other electromagnetic RF communication protocol.
  • the cellular communication network may be a fourth generation (4G) LTE, LTE Advanced (LTE-A), LTE Cat-M1 , LTE Cat-M2, NB-loT, fifth generation (5G), sixth generation (6G), and/or any other present or future developed cellular wireless network.
  • 4G fourth generation
  • LTE-A LTE Advanced
  • LTE Cat-M1 LTE Cat-M2
  • NB-loT fifth generation
  • 5G fifth generation
  • 6G sixth generation
  • any other present or future developed cellular wireless network may be any other present or future developed cellular wireless network.
  • the electronics module 100 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.
  • SIM Subscriber Identity Module
  • the electronics module 100 may have a receiving section arranged to receive the SIM card.
  • the UICC is embedded directly into a controller of the electronics module 100. That is, the UICC may be an electronic/embedded UICC (eUlCC).
  • a eUlCC 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 100 may comprise a secure element that represents an 35 embedded Universal Integrated Circuit Card (eUlCC). 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 103 is connected to the interface 101 via an analog-to-digital converter (ADC) front end 139 and an electrostatic discharge (ESD) protection circuit 141.
  • ADC analog-to-digital converter
  • ESD electrostatic discharge
  • Figure 6 is a schematic illustration of the component circuitry for the ADC front end 139.
  • the ADC front end 139 is an integrated circuit (IC) chip which converts the raw analogue biosignal received from the sensors 209, 211 into a digital signal for further processing by the controller 103.
  • IC integrated circuit
  • 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 139 includes an input 169 and an output 171.
  • Raw biosignals from the electrodes 209, 211 are input to the ADC front end 139, where received signals are processed in an ECG channel 175 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 209, 211 .
  • the output digital signals may be decimated to reduce the sampling rate prior to being passed to a serial programmable interface (SPI) 173 of the ADC front end 139.
  • SPI serial programmable interface
  • 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 177 provides base voltages for the ECG channel 175.
  • the determining of the QRS complex can be implemented for example using the known Pan Tomkins algorithm as described in Pan, Jiapu; Tompkins, Willis J. (March 1985). "A Real-Time QRS Detection Algorithm". IEEE Transactions on Biomedical Engineering. BME-32 (3): 230- 236.
  • Signals are output to the controller 103 via the SPI 173.
  • the controller 103 can also be configured to apply digital signal processing (DSP) to the digital signal from the ADC front end 139.
  • DSP digital signal processing
  • the DSP may include noise filtering additional to that carried out in the ADC front end 139 and ay also include additional processing to determine further information about the signal from the ADC front end 139.
  • the controller 103 is configured to send the biosignals to the user electronic device 300 using either of the first antenna 107, second antenna 109, or wireless communicator 159.
  • the biosignals sent to the user electronic device 300 in this example comprise the inter beat interval (IBI) values representing the time differences between successive R peaks in the measured ECG signal.
  • IBI inter beat interval
  • the user electronic device 300 in the example of Figure 7 is in the form of a mobile phone or tablet and comprises a controller 305, a memory 304, a wireless communicator 307, a display 301 , a user input unit 306, a capturing device in the form of a camera 303 and an inertial measurement unit (IMU) 309.
  • the controller 305 provides overall control to the user electronic device 300.
  • the user input unit 306 receives inputs from the user such as a user credential.
  • the memory 304 stores information for the user electronic device 300.
  • the display 301 is arranged to display a user interface for applications operable on the user electronic device 300.
  • the IMU 309 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 300 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 305 is configured to launch an application which is configured to display insights derived from the biosignal data processed by the ADC front end 139 of the electronics module 100, input to electronics module controller 103, and then transmitted from the electronics module 100.
  • the transmitted data is received by the wireless communicator 307 of the user electronic device 300 and input to the controller 305.
  • 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 600 using the wearable assembly 500.
  • the display 301 may be a presence-sensitive display and therefore may comprise the user input unit 306.
  • the presence-sensitive display may include a display component and a presencesensitive input component.
  • the presence sensitive display may be a touch-screen display arranged as part of the user interface.
  • 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 300 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 300 may include a head-mounted device such as an Augmented Reality, Virtual Reality or Mixed Reality headmounted device.
  • the user electronic device 300 may be desktop PC, workstations, television apparatus or a projector, e.g. arranged to project a display onto a surface.
  • the electronics module 100 is configured to receive raw biosignal data from the sensors 209, 211 and which are coupled to the controller 103 via the interface 101 and the ADC front end 139 for further processing and transmission to the user electronic device 300 as described above.
  • the data transmitted to the user electronics device 300 includes raw or processed biosignal data such as ECG data, heart rate, respiration data, core temperature and other insights as determined.
  • the controller 305 of the user electronics device 300 is also operable to launch an application which is configured to determine and output (e.g. display) a recovery score for the user.
  • the user interface 302 displayed by the user electronics device 300 during the recovery score test is shown in Figures 8 to 12.
  • the recovery score application displays, on the user interface 302, a prompt to the user to lie down, relax and breath normally. This instructs the user to adopt a first, resting, position.
  • the user then presses the start button 3022 to being the measurement procedure.
  • the recovery score application uses motion data received from the electronics module 100 to determine whether the user has adopted the first, resting, position.
  • the motion states may be output to the user electronics device 300 as the motion data rather than, for example, the original accelerometer values. This simplifies the processing operations performed by the user electronics device 300. This is not required in all examples, and motion data in the form of accelerometer values may be provided to the user electronics device 300 to determine the position of the user.
  • the recovery score application determines that the user has not adopted the first, resting, position, the user may be prompted visually or otherwise by the user electronics device 300 to adopt the first, resting, position.
  • this approach helps ensure user compliance with the recovery test automatically based on motion data received from the electronics module 100. This enables an accurate recovery score to be generated as the recovery score will not be affected by heartbeat data obtained while the user is not in the correct position. Human supervision by, for example, a clinician is therefore not required to perform the recovery test.
  • the recovery score application determines that the user has adopted the first, resting, position, the recovery score application transitions to the screen shown in Figure 9.
  • the recovery score application displays an ECG waveform 3023 using biosignal data transmitted by the electronics module 100 to the user electronics device 300.
  • the biosignal data received by the user electronic device 300 includes the recorded ECG data.
  • the received biosiginal data is in the form of inter-beat internal (IBI) values rather than the original ECG signals.
  • IBI inter-beat internal
  • the recovery score application records heartbeat data while the user is in the resting position for a first time period of three minutes (other time ranges are possible) and thus obtains a first sequence of heartbeat data samples of the user while in the first, resting, position.
  • a timer 3025 displays the remaining time to the user.
  • the electronics module 100 also transmits motion data to the user electronics device 300.
  • the recovery score application analyses the motion data so as to determine whether the user is remaining in the first position. This helps ensure user compliance with the recovery test throughout the testing procedure. Human supervision by, for example, a clinician is therefore not required to perform the recovery test.
  • the recovery score application may check for whether the heartbeat data indicates that an abnormal condition is present.
  • the abnormal condition may be an unexpectedly elevated, rising, or varying heartrate that would not normally be expected when a user is in the first, relaxed position.
  • the recovery score application prompts the user to restart the recovery test. If the user elects to not restart the recovery test, the heartbeat data obtained prior to the user deviating from the first position I the abnormal condition being detected may still be used to generate the recovery score. In this way, incorrect heartbeat data is automatically removed and not used to generate the recovery score. This helps to enhance the accuracy of the recovery score.
  • the recovery score application may generate a prompt to the user to seek medical advice.
  • the recovery score application transitions to the screen shown in Figure 10 after the first time period has elapsed.
  • the user interface 302 displays a prompt 3027 to the user to adopt the second position by standing up, relaxing and breathing normally. This instructs the userto adopt the second, standing, position.
  • audible and/or haptic feedback may prompt the user to adopt the standing position.
  • the recovery score application transitions to the screen in Figure 11 .
  • the recovery score application displays an ECG waveform 3029 using biosignal data transmitted by the electronics module 100 to the user electronics device 300.
  • the biosignal data received by the user electronic device 300 includes the recorded ECG data.
  • the recovery score application records heartbeat data while the user is in the second, standing, position for a second time period of three minutes (other time ranges are possible) to obtain a second sequence of heartbeat data samples for the user.
  • a timer 3031 displays the remaining time to the user.
  • the electronics module 100 also transmits motion data to the user electronics device 300.
  • the recovery score application analyses the motion data so as to determine whether the user is remaining in the second, standing, position.
  • the recovery score application may check for whether the heartbeat data indicates that an abnormal condition is present.
  • the abnormal condition may be an unexpectedly elevated, rising, or varying heartrate that would not normally be expected when a user is in the second position.
  • the recovery score application prompts the user to restart the recovery test.
  • the heartbeat data obtained prior to the user deviating from the second position I the abnormal condition being detected may still be used to generate the recovery score.
  • the recovery score application may generate a prompt to the user to seek medical advice.
  • the recovery score application uses the heartbeat data obtained over the first and second time periods to generate a recovery score for the user.
  • the recovery score application transitions to the screen shown in Figure 12.
  • the obtained heartbeat data samples comprise inter beat interval (I Bl) values that are extracted from the ECG signals. That is, the user electronics device 300 receives the extracted IBI values from the electronics module 100. In other examples, the user electronics device 300 may extract the IBI values from the received ECG signals.
  • I Bl inter beat interval
  • the first time period may be a predefined time period.
  • the first time period may be selected as appropriate by a healthcare professional. Usually a time period sufficiently long is selected so as to compensate for any minor fluctuations in the user’s heartbeat.
  • the first time period may be greater than or equal to 30 seconds, greater than or equal to 1 minute, greater than or equal to 2 minutes, or greater than or equal to 3 minutes.
  • the first time period may be less than 10 minutes, less than 7 minutes, or less than 5 minutes. In some examples, the first time period is 3 minutes.
  • the second time period is usually desired to commence quickly after the first time period. Typically the second time period commences between 1 and 10 seconds after the first time period.
  • the second time period may be a predefined time period.
  • the second time period may be selected as appropriate by a healthcare professional. Usually a time period sufficiently long is selected so as to compensate for any minor fluctuations in the user’s heartbeat.
  • the second time period may be greater than or equal to 30 seconds, greater than or equal to 1 minute, greater than or equal to 2 minutes, or greater than or equal to 3 minutes.
  • the second time period may be less than 10 minutes, less than 7 minutes, or less than 5 minutes. In some examples, the second time period is 3 minutes.
  • the user electronics device 300 will use motion data to confirm that the user has adopted the second position prior to obtaining the heartbeat data during the second time period. That is, the second time period may only commence once the user electronics device 300 has confirmed that the user has adopted the second position. However, this is not required in all aspects of the present disclosure. In some examples, it may be desirable to obtain the user’s heartbeat data quickly after they adopt the second position. Checking motion data to confirm that the user is in the second position prior to obtaining the heartbeat data may introduce a time delay which could cause this desired heartbeat data to not be obtained during the second time period.
  • the generated recovery score is used to generate an output to the user.
  • the output to the user is in the form of a recovery recommendation 3034 that gives a training recommendation to the user based on the generated recovery score .
  • the recommendation may be a recommendation to seek medical advice, take a rest day, decrease training intensity or train as normal. Other recommendations are within the scope of the present disclosure.
  • a recovery value 3033 is also displayed.
  • the recovery value 3033 may be derived from the generated recovery measure or may be separately determined.
  • the recovery value 3033 is the output of the probability density function which is described in more detail below.
  • Additional metrics are displayed to the user on the screen including the user’s orthostatic (standing) heart rate 3035, heart rate variability, 3037, mental stress score 3039, physical strain 3041 and heart health score 3041 .
  • a measure of the average heartrate, HR first of the user over the first time period is derived using the heartbeat data recorded over the first time period. This may involve determining an average inter-beat interval (IBI) value for the heartbeat data recorded over the first time period.
  • the average IBI value is in milliseconds and is typically converted into a measure of the heartrate in beats per minute by dividing 60000 by the average IBI value.
  • the average IBI value is typically the mean IBI value.
  • the mean IBI value is a measure of the sum of the IBI values divided by the total number of IBI values. In other words, the mean IBI value is determined according to the formula: where IBI is the sequence of IBI values for the user over the first time period.
  • a measure of the heartrate variability, HRV first of the user over the first time period is derived using the heartbeat data recorded over the first time period. This may involve computing the root mean square of successive differences for the IBI values.
  • the measure of the root mean square of successive differences, RMSSD, between successive heartbeats is a time domain measure of heart rate variability.
  • the RMSSD is obtained by calculating each successive time difference between heartbeats. Each of these values is then squared and the result is averaged before the square root of the total is obtained.
  • RMSSD is determined according to the formula: where IBI is the sequence of IBI values for the user over the first time period.
  • the present disclosure is not limited to the user of RMMSD as a heartrate variability measure.
  • Other heartrate variability measures that may be used with the present disclosure include the standard deviation of IBI values (SDRR), the standard deviation of differences between adjacent IBI values (SDSR), the percentage of adjacent IBI values (NN) differing by more than 25 ms (pNN25), and the percentage of adjacent IBI values (NN) differing by more than 50 ms (pNN50).
  • a measure of the average heartrate, HR second of the user over the second time period is derived using the heartbeat data recorded over the second time period. This may involve determining an average inter-beat interval (IBI) value for the heartbeat data recorded over the second time period.
  • IBI inter-beat interval
  • a measure of the heartrate variability, HRV second of the user over the second time period is derived using the heartbeat data recorded over the second time period. This may involve computing the root mean square of successive differences for the IBI values.
  • All of the heartbeat values recorded over the second time period may be used to compute the average heartrate and heartrate variability measures. This is not required in all examples, and only a subset of the heartbeat data recorded over the second time period may be used to compute these measures. For example, the first one minute of heartbeat data samples recorded when the user is in the second position may be disregarded.
  • the obtained values of HR first , HRV first ,HR second , and HRV second are used to generate the recovery score.
  • the recovery score is then increased and/or decreased based on different recovery measures that use some or all of HR first , HRV first ,HR second , and HRV second .
  • Increasing the recovery score means that the recovery measure indicates that the user is recovered.
  • Decreasing the recovery score means that the recovery measure indicates that the user is not recovered.
  • the final recovery score is used to provide a recommendation to the user as displayed in the text box 3034 in Figure 12.
  • a first recovery measure is performed. This comprises comparing HRV first and HR V second to historic measures of the heartrate variability for the user during the first and second positions.
  • a two week moving average of historic heartrate variability data (HRVhistoric first ,HRVhistoric second ) for the user is compared to the values of HRV first and HR V second .
  • the two weeks moving average is just one example and other time windows can be used to calculate the historic heartrate variability for the user.
  • the generation of the recovery score comprises comparing the sum of HRV first and HRV second to the sum of HRVhistoric first and HRVhistoric second . This is not required in all examples as HRV first may be individually compared with HRVhistoric first and HRV second may be individually compared with HRVhistoric second .
  • step S106 determines that the sum of HRV first and HRV second is greater than or equal to the sum of HRVhistoric first and HRVhistoric second , then this indicates that the user is recovered and the recovery score is increased in step S107.
  • step S106 determines that the sum of HRV first and HRV second is less than the sum of HRVhistoric first and HRVhistoric second , then this indicates that the user is not recovered and the recovery score is decreased in step S108.
  • the recovery score may be increased/decreased by a greater amount than other measures due to this strong correlation.
  • the recovery score may be increased or decreased by a value of 2.
  • step S109 a second recovery measure is performed. This comprises comparing HR first and HR second t0 historic measures of the heartrate for the user during the first and second positions.
  • a two week moving average of historic heartrate data (HRhistoric first ,HRhistoric second ) for the user is compared to the values of HR first and HR S econd -
  • the two weeks moving average is just one example and other time windows can be used to calculate the historic average heartrate for the user.
  • the generation of the recovery score comprises comparing the sum of HR first and HR second to the sum of HRhistoric first and HRhistoric second - This is not required in all examples as HR first may be individually compared with HRhistoric first and HR second may be individually compared with HRhistoric second .
  • step S109 determines that the sum of HR first and HR second is less than or equal to the sum of HRhistoric first and HRhistoric second then this indicates that the user is recovered and the recovery score is increased in step S110.
  • step S109 determines that the sum of HR first and HR second is greater than the sum of HRhistoric first and HRhistoric second . then this indicates that the user is not recovered and the recovery score is decreased in step S111 .
  • the recovery score may be increased/decreased by a lesser amount than the heartrate variability measure. For example, the recovery score may be increased or decreased by a value of 1 .
  • steps S112 to S118 a series of recovery measures are performed that consider the difference between HR second and HR first and a threshold value.
  • a third recovery measure is performed. This comprises comparing the difference between HR second and HR first to a first threshold value.
  • the difference between HR second and HR first may be referred to as the orthostatic score.
  • step S112 determines that HR second - HR first is greater than the first threshold value then the recovery score is decreased in step S113.
  • the first threshold value may be the maximum expected difference between the heartrates for the user when in the first and second positions, 0HR max .
  • 0HR max HR second max - HR first min .
  • the present disclosure is not limited to any particular value of 0HR max . This value may be user specific. In some examples, 0HR max is between 20 and 40 and is preferably 30.
  • the recovery score may be increased but this is not required in all examples.
  • step S114 a fourth recovery measure is performed. This comprises comparing the difference between HR second and HR first to a second threshold value.
  • step S114 determines that HR second - HR first is less than a second threshold value then the recovery score is decreased in step S115.
  • the second threshold value may be the minimum expected difference between the heartrates for the user when in the first and second positions, 0HR mln .
  • 0HR min HR second,min - HR first max .
  • the present disclosure is not limited to any particular value of 0HR min . This value may be user specific. In some examples, 0HR max is between 0 and 10 and is preferably 5.
  • a fourth recovery measure is performed. This comprises comparing the output of a probability density function f(HR first , HR second ) to a third threshold value.
  • the function f (HR first , HR second ) uses the difference between HR second and HR first and a non-zero constant, H, that represents a desired value of the difference between HR second and HR first to generate the output.
  • the probability density function is of the form:
  • A is a non-zero scaling constant.
  • A may be equal to
  • the probability density function is scaled such that the probability density function outputs a value between 0 and a pre-defined, and preferably intuitive, maximum value (e.g. 10).
  • S acts as a scaling constant to set the maximum value of the function.
  • S may equal 1 such that the probability density function is not scaled.
  • H is a non-zero constant that represents a desired value of the difference between the heartrates when in the first and second positions
  • ⁇ 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 heartrates for the user when in the first and second position. That is, ⁇ translates the peak of the curve of the distribution generated by the probability density function to a location representing an optimum value for the user.
  • ⁇ is a non-zero scaling constant that defines the width of the curve of the distribution generated by the probability density function;
  • ⁇ is set to be proportional to the standard deviation.
  • ⁇ 3a. This centres the peak of the distribution at a position that is 3 standard deviations from a minimum expected difference between the standing and resting heart rates for the user, and also 3 standard deviations away from a maximum expected difference between the standing and resting heart rates for the user.
  • a is determined according to the maximum expected difference between heartrates for the user when in the first and second positions, 0HR max , and the minimum expected difference between heartrates for the user when in the first and second positoins, 0HR min .
  • 0HR max and 0HR min are as defined above.
  • a is determined by calculating (OHR max - OHR mm )/ C , where C is a non-zero constant that represents the number of standard deviations required to get from 0HR mln to ⁇ and from ⁇ to 0HR max .
  • C is a number greater than 0.
  • Preferably, C 6.
  • the present disclosure is not limited to any particular value of 0HR max and 0HR mln . These values are generally user specific. However, in some examples, the difference between 0HR max and 0HR min is between 20 and 50, preferably still between 25 and 40, and preferably still is 30.
  • ⁇ is proportional to the value of ⁇ and so will vary as ⁇ varies. In some examples, ⁇ is between 5 and 25. ⁇ is between 10 and 20. ⁇ is 15.
  • the function f(HR first ,HR second ) is of the form:
  • the function f(HR first ,HR second ) is of the form:
  • the function f(HR first ,HR second ) is of the form:
  • the output of the probability density function is also the numerical component of the recovery score 3033 that is displayed by the user interface 302. If step S116 determines that the output of the probability density function f(HR first , HR second ) is less than the third threshold value, then the recovery score is decreased in step S117.
  • step S116 determines that the output of the probability density function of f(HR first , HR second ) is greater than the third threshold value, then the recovery score is increased in step S118.
  • the present disclosure is not limited to any particular threshold value as it is generally user specific and depends on the scaling used for the probability density function.
  • the third threshold value is between 0 and 10, and is preferably 5.
  • the recovery score may be increased/decreased by a lesser amount than the heartrate variability measure.
  • the recovery score may be increased or decreased by a value of 1 .
  • a fifth recovery measure is performed. This comprises comparing the recovery score as determined from the first to fourth recovery measures to a fourth threshold value.
  • step S119 determines that the recovery score is greater than or equal to a fourth threshold value (e.g. 2)
  • a fourth threshold value e.g. 2
  • the difference between HR second and HRhistoric second is compared to a fifth threshold value in step S120. If the difference between HR second and HRhistoric second is greater than the fifth threshold value, then the recovery score is decreased in step S121.
  • the present disclosure is not limited to any particular value of the fourth or fifth threshold value.
  • the fourth threshold value is between 1 and 5 and is preferably 2.
  • the fifth threshold value is between 2 and 8 and is preferably 5.
  • a sixth recovery measure is performed. This comprises comparing the difference between HR second and HRhistoric second to a sixth threshold value. If the difference between HR S econd and HRhistoric second is greater than the sixth threshold value, then the recovery score is decreased or may otherwise be set to a predefined low value (e.g. 1) in step S123 to indicate that the user is under recovered.
  • a predefined low value e.g. 1
  • the present disclosure is not limited to any particular value of the sixth threshold value. Generally the sixth threshold value is between 5 and 15 and is preferably 10.
  • the recovery score may be set to a certain low value rather than increased or decreased.
  • step S124 the recovery score as determined according to the first to sixth recovery measures is used to generate a recovery recommendation.
  • the recovery recommendation may be determined according to the following table:
  • step S125 the recovery score is output to the user.
  • the recovery measures above are just examples. All six recovery measures are not required. One, a subset, or all of the recovery measures listed above may be used. The order of recovery measures is just an example. A different order of recovery measures could also be used.
  • the above example uses heartbeat data from both the first and second time period to generate the recovery score. This is not required in all examples if, for example, the recovery test terminates before the second time period. Only heartbeat data and heartrate variability data from the first time period may be used to generate the recovery score. This may comprise comparing HR first to HRhistoric first .
  • FIG 14 there is shown an example method of performing a recovery for a user.
  • the user may elect to take a recovery test via the user interface 302 as explained above in relation to Figures 8 to 12.
  • the user is prompted to adopt the first position.
  • Step S201 comprises obtaining motion data for the user.
  • Step S202 comprises determining, from the motion data, whether the user has adopted the first, resting position. If the user has not adopted the first position, the method returns to step S201 . In this way, further motion data is obtained and analysed to see whether the user has now adopted the first position.
  • Step S203 comprises obtaining heartbeat data for the user over a first time period.
  • Step S204 comprises using the heartbeat data obtained over the first time period to generate a recovery score for the user.
  • Generating the recovery score may involve deriving a measure of the average heartrate of the user over the first time period. This average heartrate of the user may be used to generate the recovery score. The average heartrate of the user may be compared to a historic average heartrate of the user.
  • Generating the recovery score may involve deriving a measure of the heartrate variability of the user over the first time period.
  • the heartrate variability measure may be used to generate the recovery score.
  • the heartrate variability measure compared to a historic heartrate variability for the user.
  • the average heartrate of the user and the heartrate variability of the user over the first time period may be used to generate the recovery score for the user.
  • Figures 15A to 15B show another example method of generating a recovery score for a user.
  • Steps S301 to S303 correspond to Steps S201 to S203 in Figure 14.
  • Step S304 comprises obtaining motion data for the user over the first time period.
  • Step S305 comprises determining from the motion data whether the user remains in the first position during the first time period.
  • Step S306 to prompt the userto restart the recovery test such as by returning to step S301 .
  • the heartbeat data obtained prior to the user moving out of the first position may still be used to generate the recovery score.
  • the method may comprise generating a prompt to the user to seek medical advice. If an abnormal condition is not present, the user is then prompted to adopt a second position.
  • the second position may be a standing position.
  • Step S307 comprises obtaining heartbeat data for the user over a second time period.
  • Step S308 comprises obtaining motion data for the user over the second time period.
  • Step S309 comprises determining from the motion data whether the user remains in the second position during the second time period.
  • step S310 prompt the user to restart the recovery test such as by proceeding to step S301 . If the user elects to not restart the recovery test, the heartbeat data obtained prior to the user moving out of the second position may still be used to generate the recovery score. If the heartbeat data indicates a potential concern for the heartbeat such as an overly elevated heartrate, the method may comprise generating a prompt to the user to seek medical advice.
  • Step S311 comprises using the heartbeat data obtained over the first time period and the heartbeat data obtained over the second time period to generate a recovery score for the user. This may involve using one or more of the recovery measures described above in relation to Figures 13A to 13D
  • Figure 16 shows another example method according to aspects of the present disclosure. This method is similar to that of Figure 14, but in this example a check is not required to initially be performed to confirm that the user is in the first position before obtaining the heartbeat data for the user over the first time period.
  • Step S401 comprises obtaining heartbeat data for a user over a first time period.
  • Step S402 comprises obtaining motion data for the user over the first time period.
  • Step S403 comprises determining, from the motion data, whether the user has deviated from a first position during the first time period.
  • Step S404 comprises generating a prompt to the user to restart the recovery test. If the user remains in the first position during the first time period, the method proceeds to step S405.
  • Step S405 comprises using the heartbeat data obtained over the first time period to generate a recovery score for the user.
  • FIG. 17 there is shown an example method of generating a recovery score for a user according to aspects of the present disclosure.
  • Step S501 comprises obtaining a measure, HR first , of the heartrate of the user when in a first position.
  • Step S502 comprises obtaining a measure, HRV first , ofthe heartrate variability of the userwhen in the first position.
  • Step S503 comprises generating a recovery score for the user using HR first , and HRV first .
  • FIG. 18 there is shown an example method of generating a recovery score for a user according to aspects of the present disclosure.
  • Step S601 comprises obtaining a measure, HR first , of the heartrate of the user when in a first position.
  • Step S602 comprises obtaining a measure, HRV first , ofthe heartrate variability of the userwhen in the first position.
  • Step S603 comprises obtaining a measure, HR second , of the heartrate of the user when in a second position.
  • Step S604 comprises obtaining a measure, HRV second , of the heartrate variability of the user when in the second position.
  • Step S605 comprises generating a recovery score for the user using HR first , HRV first ,HR second , and HRV second .
  • the method comprises obtaining motion data for the user (S201).
  • the method comprises determining, from the motion data, whether the user has adopted a first position (S202). If the user has adopted the first position: the method further comprises obtaining heartbeat data for the user over a first time period (S203); and using the heartbeat data obtained over the first time period to generate a recovery score for the user (S204).
  • the recovery score may be generated using heartrate and heartrate variability data generated during the first time period and optionally a second period when the user adopts a second position.
  • 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.

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  • Databases & Information Systems (AREA)
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  • Data Mining & Analysis (AREA)
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  • Epidemiology (AREA)
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  • Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

Procédé et système de génération d'un score de récupération pour un utilisateur. Le procédé comprend l'obtention d'une mesure, HRpremière, de la fréquence cardiaque de l'utilisateur lorsqu'il se trouve dans une première position (S601). Le procédé comprend l'obtention d'une mesure, HRVpremière, de la variabilité de la fréquence cardiaque de l'utilisateur lorsqu'il se trouve dans la première position (S602). Le procédé comprend l'obtention d'une mesure, HRseconde, de la fréquence cardiaque de l'utilisateur lorsqu'il se trouve dans une seconde position (S603). Le procédé comprend l'obtention d'une mesure, HRVseconde, de la variabilité de la fréquence cardiaque de l'utilisateur lorsqu'il se trouve dans la seconde position (S604). Le procédé comprend en outre la génération du score de récupération à l'aide de HRpremière, HRVpremière, HRseconde et HRVseconde (S605).
EP21830325.3A 2020-12-15 2021-12-13 Procédé et système de génération d'un score de récupération pour un utilisateur Pending EP4262544A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB2019778.6A GB2605556B (en) 2020-12-15 2020-12-15 Method and system for performing a recovering test and generating a recovery score for a user
PCT/GB2021/053262 WO2022129879A1 (fr) 2020-12-15 2021-12-13 Procédé et système de génération d'un score de récupération pour un utilisateur

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EP4262544A1 true EP4262544A1 (fr) 2023-10-25

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Publication number Priority date Publication date Assignee Title
WO2024092214A1 (fr) * 2022-10-28 2024-05-02 Ohio State Innovation Foundation Procédés et systèmes de surveillance de signaux biomagnétiques

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FI119618B (fi) * 2006-05-03 2009-01-30 Polar Electro Oy Menetelmä, käyttäjäkohtainen suoritemittari, järjestelmä ja tietokoneohjelmistotuote
US9220444B2 (en) * 2010-06-07 2015-12-29 Zephyr Technology Corporation System method and device for determining the risk of dehydration
AT511044B1 (de) * 2011-02-09 2013-06-15 Pulse7 Gmbh Verfahren und vorrichtung zur bestimmung des leistungspotentials einer testperson
US9743848B2 (en) * 2015-06-25 2017-08-29 Whoop, Inc. Heart rate variability with sleep detection
US20160058378A1 (en) * 2013-10-24 2016-03-03 JayBird LLC System and method for providing an interpreted recovery score

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GB202019778D0 (en) 2021-01-27
WO2022129879A1 (fr) 2022-06-23
GB2605556A (en) 2022-10-12
GB2605556B (en) 2024-01-31

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