Visualizing, Scoring, Recording, and Analyzing Sleep Data and Hypnograms

• US 20170055899A1
• Filed: 08/26/2016
• Published: 03/02/2017
• Est. Priority Date: 08/28/2015
• Status: Active Grant

• Current Assignee: Awarables, Inc.
• Original Assignee: Awarables, Inc.
• Inventors: Upender, Raghu, Bandyopadhyay, Amrit, Blankenship, Gilmer, Upender, Madhvi
• Granted Patent: US 10,582,890 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2503/12 Healthy persons not otherwise provided for, e.g. subjects of a marketing survey
• CPC Class Codes: A61B 2503/42 for laboratory research
• CPC Class Codes: A61B 2505/09 Rehabilitation or training
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• 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 5/282 Holders for multiple electrodes for introduction into the body A61B5/287
• CPC Class Codes: A61B 5/333 Recording apparatus specially adapted therefor
• 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 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/6804 Garments; Clothes
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 7/003 Detecting lung or respiration noise

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for visualizing, scoring, recording, and analyzing sleep data and hypnograms. In some implementations, a method includes generating and providing a representation of sleep stages that includes a sequence of elements indicating a progression of the sleep stages over time during a sleep session. In some implementations, a method includes generating and providing one or more scores based on analysis of the sleep session. In some implementations, a wearable body data recorder includes a plurality of sensors and is configured to measure and process sensor data obtained during a sleep session of a subject.

Claims

1. A method performed by one or more computing devices, the method comprising:

accessing, by the one or more computing devices, data indicating sleep stages of a particular person during a sleep session;

generating, by the one or more computing devices, data for a visual representation of the sleep stages of the sleep session, wherein the visual representation includes a ribbon having a sequence of elements indicating a progression of the sleep stages over time during the sleep session; and

providing, by the one or more computing devices, the data for the visual representation for display on a display device.

2. The method of claim 1, further comprising receiving, by a user device, a short-range wireless signal from a body data recorder worn by the particular person,

wherein the data indicating the sleep stages is determined based on the sensor data, and the visual representation is displayed by the user device.

3. The method of claim 1, further comprising accessing data indicating sleep stages of multiple different sleep sessions of the particular person;

wherein generating the data for the visual representation comprises generating data for a visual representation of the multiple different sleep sessions, wherein the visual representation includes, for each sleep session, a ribbon having a sequence of horizontal elements indicating a progression of the sleep stages over time during the sleep session, wherein the ribbons for the multiple sleep sessions are arranged in a column.

4. The method of claim 3, wherein the ribbons for the multiple sleep sessions are horizontally aligned so that (i) a same horizontal position indicates a same time of day for each of the sleep sessions, or (ii) a same horizontal position indicates a start of each of the sleep sessions;

and

wherein the number of sleep sessions displayed in the visual representation and horizontal alignment can be changed to view multiple sleep session sleep architectures or sleep signatures.

5. The method of claim 1, wherein the elements are sized according to the respective durations of the segments corresponding to the elements, and each of the elements is color-coded to indicate the sleep stage of the corresponding segment.

6. The method of claim 1, wherein the sleep stages include a wake stage, a rapid eye movement (REM) stage, and two or more different types of non-REM stages of sleep.

7. The method of claim 1, wherein generating the data for the visual representation of the sleep stages comprises generating data for a visual representation that includes indicators of events occurring during the sleep session, the indicators being aligned relative to the elements to indicate, with respect to the elements, times that the events occurred, wherein the indicators are indicators of sleep apnea events.

8. The method of claim 1, wherein accessing the data indicating the sleep stages comprises receiving the data at a user device from a server system over a network;

and

displaying the visual representation on a screen of the user device.

9. A device comprising:

at least two EKG contacts to measure EKG signals of a subject during a sleep session;

a processing module configured to move with the subject, the processing module comprising at least one processor and at least one data storage device,

one or more sensors, the one or more sensors being configured to detect a condition of the subject or an environment proximate to the subject; and

wherein the processing module is configured to record sensor data during the sleep session of the subject, the sensor data indicating (i) EKG signals detected using the EKG contacts and (ii) the condition detected using the one or more sensors, the processing module being configured to record data indicating timing of the condition of the subject or environment relative to the EKG signals detected.

10. The device of claim 9, wherein the device comprises a wearable housing that houses the one or more sensors and the processing module, the housing being configured to receive the EKG signals detected through the EKG contacts when worn by the subject.

11. The device of claim 9, further comprising:

a battery; and

a short-range wireless transceiver, wherein the device is configured to transmit the sensor data using the short-range transceiver,

wherein the device is configured to detect, record, and transmit the sensor data as a wireless and self-contained system.

12. The device of claim 9, wherein the one or more sensors comprise a microphone, wherein the processing module is configured to record data indicating sounds detected by the microphone during the sleep session, wherein the processing module is configured to (i) detect apnea events of the subject based on signals detected by the microphone and (ii) store data indicating the apnea events.

13. The device of claim 9, wherein the one or more sensors comprise a light sensor, wherein the processing module is configured to record ambient light levels detected by the light sensor during the sleep session.

14. The device of claim 9, wherein the one or more sensors comprise a temperature sensor, wherein the processing module is configured to record temperatures detected by the temperature sensor during the sleep session.

15. The device of claim 9, wherein the one or more sensors comprise a motion sensor, wherein the processing module is configured to record movement of the subject detected by the motion sensor during the sleep session.

16. A method performed by one or more computing devices, the method comprising:

accessing sleep stage data generated from sensor data measured during a sleep session of a subject, the sleep stage data indicating periods of the sleep session and corresponding sleep stages during the periods;

determining one or more scores based on analysis of the sleep session; and

providing an indication of the determined one or more scores for display at a user device.

17. The method of claim 16, wherein determining the one or more scores comprises determining at least one of the scores in the group consisting of:

a sleep onset latency score indicating an amount of time between a wake stage and a first sleep stage that occurs after the wake stage;

a total sleep time representing a total time the subject is in non-wake sleep stages during the sleep session;

a stage duration score indicating an amount of time during the sleep session that the subject spent in a particular sleep stage;

a stage occurrence score indicating a number of stable occurrences of a particular sleep stage or transitions to or from the particular sleep stage;

18. The method of claim 16, wherein determining the one or more scores comprises determining at least one of the scores in the group consisting of:

a cumulative sleep score based on a sum of durations of segments of the sleep session designated as REM stages and durations of segments designated as slow wave sleep segments.

a REM Score representing the architecture of a subject'"'"'s REM stages, wherein the REM score is determined based on (i) a total duration of segments designated as REM stages during the sleep session and (ii) the longest stable REM segment during the sleep session; and

a slow wave sleep (SWS) score representing the architecture of a subject'"'"'s deep sleep, wherein the SWS Score is determined based on (i) a total duration of segments designated as SWS stages during the sleep session and (ii) the longest stable SWS segment during the sleep session.

19. The method of claim 16, wherein determining the one or more scores comprises determining a number of events of a particular type that occurred during the sleep session, and durations of the events, wherein the particular type of events is a snoring event or an apnea event.

20. The method of claim 16, wherein determining the one or more scores comprises determining a sleep onset time, determining a final wake segment in the sleep session, and determining a Wake After Sleep Onset (WASO) score as a sum of all segment durations for segments designated as wake segments, excluding those before the sleep onset time and the final wake segment.