Heart rate variability with sleep detection

• US 9,750,415 B2
• Filed: 07/12/2016
• Issued: 09/05/2017
• Est. Priority Date: 09/04/2012
• Status: Active Grant

• Current Assignee: Whoop, Inc.
• Original Assignee: Whoop, Inc.
• Inventors: Breslow, Emily Rachel, Capodilupo, John, Ahmed, William
• Primary Examiner(s): GETZOW, SCOTT M
• Application Number:
  US15/207,924
• Publication Number:
  US 20160374569A1
• Time in Patent Office: 420 Days
• CPC Class Codes: A61B 2560/0214 of power generation or supply
• CPC Class Codes: A61B 2560/0443 Modular apparatus
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/0238 Optical sensor arrangements for performing transmission measurements on body tissue
• CPC Class Codes: A61B 2562/0257 Proximity sensors
• CPC Class Codes: A61B 2562/227 Sensors with electrical connectors
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0082 adapted for particular medical purposes
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02427 Details of sensor
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0255 Recording instruments specially adapted therefor
• CPC Class Codes: A61B 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/441 : Skin evaluation, e.g. for skin disorder diagnosis
• CPC Class Codes: A61B 5/4806 : Sleep evaluation A61B5/4821 takes precedence; devices for inducing sleep A61M21/02
• CPC Class Codes: A61B 5/4809 : Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/4812 : Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/4815 : Sleep quality
• CPC Class Codes: A61B 5/4866 : Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/681 : Wristwatch-type devices
• CPC Class Codes: A61B 5/6813 : Specially adapted to be attached to a specific body part A61B5/6802 takes precedence
• CPC Class Codes: A61B 5/6824 : Arm or wrist
• CPC Class Codes: A61B 5/6829 : Foot or ankle
• CPC Class Codes: A61B 5/6831 : Straps, bands or harnesses
• CPC Class Codes: A61B 5/684 : Indicating the position of the sensor on the body
• CPC Class Codes: A61B 5/6844 : Monitoring or controlling distance between sensor and tissue
• CPC Class Codes: A61B 5/7221 : Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/7267 : involving training the classification device
• CPC Class Codes: A61B 5/7278 : Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/7282 : Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/7285 : for synchronising or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal A61B6/5205, A61B6/541, A61B8/5207, A61B8/543 take precedence
• CPC Class Codes: A61B 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7475 : User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A63B 2024/0065 : Evaluating the fitness, e.g. fitness level or fitness index
• CPC Class Codes: A63B 2220/803 : Motion sensors
• CPC Class Codes: A63B 2225/50 : Wireless data transmission, e.g. by radio transmitters or telemetry
• CPC Class Codes: A63B 2230/06 : heartbeat rate only
• CPC Class Codes: A63B 24/0003 : Analysing the course of a movement or motion sequences during an exercise or trainings sequence, e.g. swing for golf or tennis
• CPC Class Codes: A63B 24/0062 : Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: A63B 24/0075 : Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
• CPC Class Codes: A63B 24/0087 : Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load
• CPC Class Codes: G06F 1/163 : Wearable computers, e.g. on a belt
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/40 : relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 40/63 : for local operation

Abstract

A system uses continuous tracking of sleep activity and heart rate activity to evaluate heart rate variability immediately before transitioning to an awake state, e.g., at the end of the last phase of deep sleep. In particular, a wearable, continuous physiological monitoring system as described herein includes one or more sensors to detect sleep states, the transitions between sleep states, and the transitions from a sleep state to an awake state for a user. This information can be used in conjunction with continuously monitored heart rate data to calculate heart rate variability of the user at the end of the last phase of sleep preceding the user waking up. By using the history of heart rate data in conjunction with sleep activity in this manner, an accurate and consistent recovery score can be calculated based on heart rate variability.

Claims

1. A method of operating a wearable, continuous physiological monitoring system comprising:

monitoring sleep states of a user over a period of time;

monitoring a heart rate of the user substantially continuously with the wearable, continuous physiological monitoring system over the period of time;

recording heart rate data within the period of time;

detecting, within the period of time, a waking event at a transition from a last sleep state of the user to an awake state;

determining an end of a most recent slow wave sleep state occurring most recently before the waking event

calculating a heart rate variability of the user at the end of the most recent slow wave sleep state preceding the waking event based upon the heart rate data; and

calculating a recovery score for the user based upon the heart rate variability from the end of the most recent slow wave sleep state preceding the waking event, the recovery score indicative of a level of recovery of the user'"'"'s body and health after a period of physical exertion.

2. The method of claim 1 further comprising calculating a duration of sleep and using the duration to calculate the recovery score.

3. The method of claim 1 wherein monitoring sleep states is based on a signal received from an accelerometer of the wearable, continuous physiological monitoring system.

4. The method of claim 3 wherein detecting the waking event is based on the signal received from the accelerometer.

5. The method of claim 1 wherein at least one of monitoring sleep states and detecting the waking event is based upon the heart rate data.

6. The method of claim 1 wherein recording the heart rate data includes recording the heart rate data continuously without calculating the heart rate variability.

7. The method of claim 1 wherein the wearable, continuous physiological monitoring system includes a processor, one or more light emitting diodes, and one or more light detectors configured to obtain the heart rate data from the user.

8. The method of claim 1 further comprising calculating a sleep need score estimating an amount of sleep needed by the user in a next night, and communicating the sleep need score to user.

9. A system comprising:

a wearable housing;

one or more sensors in the wearable housing; and

a processor in communication with the one or more sensors, the processor configured to receive data from the one or more sensors to monitor sleep states of a user wearing the wearable housing over a period of time, to monitor a heart rate of the user substantially continuously over the period of time, to detect a waking event at a transition from a last sleep state of the user to an awake state, to determine an end of a most recent slow wave sleep state occurring most recently before the waking event, to calculate heart rate variability of the user at a moment in the most recent slow wave sleep state preceding the waking event based upon the heart rate, and to calculate a recovery score for the user based upon the heart rate variability from the most recent slow wave sleep state preceding the waking event.

10. The system of claim 9 wherein the one or more sensors include a light detector configured to provide heart rate data to the processor for calculating the heart rate variability.

11. The system of claim 10 wherein the processor is configured to detect the waking event based on the data from the light detector.

12. The system of claim 10 wherein the processor is configured to monitor sleep states of the user based on the data from the light detector.

13. The system of claim 9 wherein the one or more sensors include an accelerometer configured to provide data to the processor for at least one of monitoring sleep states and detecting the waking event.

14. The system of claim 9 further comprising a light source coupled to the wearable housing, the light source directed toward a skin on an appendage of the user.

15. The system of claim 9, wherein the processor is within the wearable housing.

16. A computer program product for determining physical recovery of a user wearing a continuous physiological monitoring device, the computer program product comprising computer executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs the steps of:

monitoring sleep states of the user;

monitoring a heart rate of the user substantially continuously;

recording the heart rate as heart rate data;

detecting a waking event at a transition from a last sleep state of the user to an awake state;

determining an end of a most recent slow wave sleep state occurring most recently before the waking event;

calculating a heart rate variability of the user at a moment in the most recent slow wave sleep state preceding the waking event based upon the heart rate; and

calculating a recovery score for the user based upon the heart rate variability from the most recent slow wave sleep state preceding the waking event.

17. The computer program product of claim 16 further comprising code that performs the step of calculating a duration of sleep and using the duration to calculate the recovery score.

18. The computer program product of claim 16 further comprising code that performs the step of monitoring sleep states and detecting the waking event using data received from an accelerometer coupled to the user.

19. The computer program product of claim 16 further comprising code that performs the step of monitoring sleep states using the heart rate data.

20. The computer program product of claim 16 further comprising code that performs the step of detecting the waking event using the heart rate data.