# US 9,750,415 B2 · Heart rate variability with sleep detection

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- Number: US 9,750,415 B2
- Document ID: US9750415B2
- Status: Granted
- Kind: B2
- Application number: 15/207,924
- Filed: 2016-07-12
- Published: 2016-12-29
- Granted: 2017-09-05
- Earliest claimed: 2015-06-25
- Assignees: Whoop, Inc.
- Applicants: Whoop, Inc.
- Inventors: Emily Rachel Breslow; John Capodilupo; William Ahmed
- Web page: https://patentgrep.com/patent/US9750415B2

## CPC

- G16H 20/30: relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
- A61B 5/0004: {characterised by the type of physiological signal transmitted}
- A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet}
- A61B 5/0082: {adapted for particular medical purposes}
- A61B 5/0205: Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B 5/02405: {Determining heart rate variability}
- A61B 5/02416: {using photoplethysmograph signals, e.g. generated by infrared radiation (A61B5/14552 takes precedence)}
- A61B 5/02427: {Details of sensor}
- A61B 5/02438: {with portable devices, e.g. worn by the patient}
- A61B 5/0255: Recording instruments specially adapted therefor
- A61B 5/0533: Measuring galvanic skin response
- A61B 5/11: Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb {(A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721)}
- A61B 5/1112: {Global tracking of patients, e.g. by using GPS}
- A61B 5/1118: {Determining activity level}
- A61B 5/441: {Skin evaluation, e.g. for skin disorder diagnosis}
- A61B 5/4806: {Sleep evaluation (A61B5/4821 takes precedence; devices for inducing sleep A61M21/02)}
- A61B 5/4809: {Sleep detection, i.e. determining whether a subject is asleep or not}
- A61B 5/4812: {Detecting sleep stages or cycles}
- A61B 5/4815: {Sleep quality}
- A61B 5/681: {Wristwatch-type devices}
- A61B 5/6813: {Specially adapted to be attached to a specific body part (A61B5/6802 takes precedence)}
- A61B 5/6824: {Arm or wrist}
- A61B 5/6829: {Foot or ankle}
- A61B 5/6831: {Straps, bands or harnesses}
- A61B 5/684: {Indicating the position of the sensor on the body}
- A61B 5/6844: {Monitoring or controlling distance between sensor and tissue}
- A61B 5/7221: {Determining signal validity, reliability or quality (preventing, reducing or removing noise induced by motion artefacts A61B5/7207; noise originating from a therapeutic or surgical apparatus A61B5/7217)}
- A61B 5/7267: {involving training the classification device}
- A61B 5/7278: {Artificial waveform generation or derivation, e.g. synthesizing signals from measured signals}
- A61B 5/7282: {Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818)}
- A61B 5/7285: {for synchronizing or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal}
- A61B 5/742: {using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339)}
- A61B 5/7475: {User input or interface means, e.g. keyboard, pointing device, joystick}
- 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}
- 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}
- A63B 24/0075: {Means for generating exercise programmes or schemes, e.g. computerized virtual trainer, e.g. using expert databases}
- A63B 24/0087: {Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load}
- G06F 1/163: {Wearable computers, e.g. on a belt}
- G16H 20/40: relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
- G16H 40/63: for local operation
- A61B 5/4866: {Evaluating metabolism (using breath test A61B5/083)}
- A61B 2560/0214: of power generation or supply
- A61B 2560/0443: Modular apparatus
- A61B 2560/0475: Special features of memory means, e.g. removable memory cards
- A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
- A61B 2562/0238: Optical sensor arrangements for performing transmission measurements on body tissue
- A61B 2562/0257: Proximity sensors
- A61B 2562/227: Sensors with electrical connectors
- A63B 2024/0065: {Evaluating the fitness, e.g. fitness level or fitness index}
- A63B 2220/803: Motion sensors
- A63B 2225/50: Wireless data transmission, e.g. by radio transmitters or telemetry
- A63B 2230/06: heartbeat rate only
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- A63B: APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT (apparatus for passive exercising, massage A61H)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## 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

### Claim 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.

### Claim 2 (depends on 1)

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

### Claim 3 (depends on 1)

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.

### Claim 4 (depends on 3)

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

### Claim 5 (depends on 1)

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.

### Claim 6 (depends on 1)

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

### Claim 7 (depends on 1)

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.

### Claim 8 (depends on 1)

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.

### Claim 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.

### Claim 10 (depends on 9)

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.

### Claim 11 (depends on 10)

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

### Claim 12 (depends on 10)

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.

### Claim 13 (depends on 9)

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.

### Claim 14 (depends on 9)

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.

### Claim 15 (depends on 9)

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

### Claim 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.

### Claim 17 (depends on 16)

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.

### Claim 18 (depends on 16)

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.

### Claim 19 (depends on 16)

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

### Claim 20 (depends on 16)

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