System and method for snoring detection using low power motion sensor

• US 10,617,364 B2
• Filed: 12/06/2016
• Issued: 04/14/2020
• Est. Priority Date: 10/27/2016
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Li, Yelei, Wiggins, Matthew C., De Proft, Anabel M.
• Primary Examiner(s): Hindenburg, Max F
• Application Number:
  US15/370,468
• Publication Number:
  US 20180116606A1
• Time in Patent Office: 1,225 Days
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/4806 Sleep evaluation A61B5/4821 takes precedence; devices for inducing sleep A61M21/02
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• 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 5/7405 using sound
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7455 characterised by tactile indication, e.g. vibration or electrical stimulation

Abstract

Provided is an electronic device to monitor a user'"'"'s biological measurements, where a sensor is configured to acquire a raw signal from a user, and the electronic device determines a snoring signal from the raw signal by appropriately processing the raw signal.

Claims

1. A method comprising:

detecting a raw signal from a user via a motion sensor;

determining a snoring signal from the raw signal based on an adaptive frequency threshold; and

providing feedback to the user based on the snoring signal,

wherein;

the feedback comprises visual instruction to the user regarding sleeping position provided prior to determining the snoring signal.

2. The method of claim 1, wherein the feedback is one of a vibration, an audio alert, and visual alert.

3. The method of claim 1, wherein a microphone is used to detect audible sound from the user to supplement the detecting of the raw signal.

4. The method of claim 1, wherein the raw signal is detected by one of an accelerometer and a gyrometer.

5. The method of claim 1, comprising pre-processing the raw signal with one of time-domain processing and time-frequency processing.

6. The method of claim 5, wherein the time-domain processing comprises one of band-pass filtering and high-pass filtering.

7. The method of claim 5, wherein the time-frequency processing comprises wavelets coefficient reconstruction.

8. The method of claim 1, comprising, if there are multiple channels for monitoring the raw signal, selecting one of the multiple channels for monitoring the raw signal.

9. The method of claim 1, comprising tracking a body position of the user.

10. A non-transitory machine-readable medium storing machine executable instructions that when executed causes a computing system to control operations comprising:

detecting a raw signal from a user via a motion sensor;

determining a snoring signal from the raw signal based on an adaptive frequency threshold; and

providing feedback to the user based on the snoring signal,

wherein;

the feedback comprises visual instruction to the user regarding sleeping position provided prior to determining the snoring signal.

18. The non-transitory machine-readable medium storing machine executable instructions that when executed causes a computing system to control operations of claim 10, comprising pre-processing the raw signal with one of time-domain processing and time-frequency processing, wherein the time-frequency processing comprises wavelets coefficient reconstruction.

19. The non-transitory machine-readable medium storing machine executable instructions that when executed causes a computing system to control operations of claim 10, comprising tracking a body position of the user.

11. An electronic device comprising:

a motion sensor configured to detect a raw signal from a user;

a processor configured to determine a snoring signal from the raw signal based on an adaptive frequency threshold; and

an output device configured to provide feedback to the user based on the snoring signal,

wherein;

the feedback comprises visual instruction to the user regarding sleeping position provided prior to determining the snoring signal.

12. The electronic device of claim 11, wherein the output device is one or more of a vibration module, a speaker, and a visual display.

13. The electronic device of claim 11, wherein the motion sensor is one of an accelerometer and a gyrometer.

14. The electronic device of claim 11, wherein the processor is configured to pre-process the raw signal with one of time-domain processing and time-frequency processing.

15. The electronic device of claim 14, wherein the time-frequency processing comprises wavelets coefficient reconstruction.

16. The electronic device of claim 11, wherein, if there are multiple channels for monitoring the raw signal, the processor is configured to select one of the multiple channels for monitoring the raw signal.

17. The electronic device of claim 12, wherein the electronic device is configured to track a body position of the user.

20. The electronic device of claim 11, wherein the processor is configured to track a body position of the user.