CONTACTLESS NON-INVASIVE ANALYZER OF BREATHING SOUNDS

• US 20130060100A1
• Filed: 05/12/2011
• Published: 03/07/2013
• Est. Priority Date: 05/13/2010
• Status: Abandoned Application

• Current Assignee: Sensewiser, Ltd.
• Original Assignee: Sensewiser, Ltd.
• Inventors: Heller, Zeev, Wurm, Arie John Martin, Scheim, Jacob
• Application Number:
  US13/697,538
• Publication Number:
  US 20130060100A1
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/0823 Detecting or evaluating cough events
• CPC Class Codes: A61B 5/1113 Local tracking of patients, e.g. in a hospital or private home
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 7/003 Detecting lung or respiration noise

Abstract

A device and method for monitoring and analyzing breathing sounds, the device including at least one microphone adapted and configured for placement adjacent a body to be monitored for contactless recording of breathing sounds, a motion detector using an ultrasound distance sensor to detect the patient body motions, and a processor coupled to the microphones and the motion detector for receiving and processing the breathing sounds and patient motions to detect abnormal breathing events.

Claims

1. A device for monitoring and analyzing breathing sounds, the device comprising:

at least one microphone placed adjacent a body to be monitored for contactless recording of breathing sounds;

a motion detector to detect motions of said body;

a processor coupled to said microphones and said motion detector for receiving and processing said breathing sounds and concurrent detected motions to detect abnormal breathing events.

2. The device according to claim 1, further comprising means for recording said detected breathing events in an events log.

3. The device according to claim 1, wherein said motion detector includes an ultrasonic distance sensor.

4. The device according to claim 1, wherein said processor includes a module for distinguishing said breathing sounds from background sounds.

5. The device according to claim 1, further comprising a spatial filter for determining direction from which sounds are received in said microphones.

6. The device according to claim 1, further comprising a time domain filter for filtering spectral noises from the signal and maximizing the breathing signal quality.

7. The device according to claim 1, further comprising a sound identifier including:

a module for calculating a sound events marker;

a basic motion and breathing sound correlation filter; and

a sound event analyzer.

8. The device according to claim 7, wherein said sound event analyzer includes:

a time domain analyzer;

a frequency domain analyzer; and

a sound and motion correlation filter.

9. The device according to claim 1, wherein said processor is programmed to perform frequency analysis measuring power distribution in a sound event using a bi-level image of the sound event spectrogram and an FFT of the image to detect repeating patterns.

18. The device according to claim 1, wherein said abnormal breathing events are selected from the group including coughs, wheezes and breathing rate changes.

19. The device according to claim 2, wherein said motion detector includes an ultrasonic distance sensor.

10. A method for monitoring and analyzing breathing sounds, the method comprising:

placing at least one microphone adjacent a body to be monitored;

recording breathing sounds from said body without contacting said body;

detecting motion of said body; and

receiving and processing said breathing sounds correlated with said patient motions in a processor to detect abnormal breathing events of said body.

11. The method according to claim 10, wherein said step of detection motion includes detecting motion of said body using an ultrasound distance sensor.

12. The method according to claim 10, further comprising recording said analyzed breathing sounds in an events log.

13. The method according to claim 10, further comprising distinguishing said breathing sounds from background sounds in said recorded sounds, and analyzing said breathing sounds to detect abnormal breath events including but not limited to coughs wheezes and breathing rate changes.

14. The method according to claim 10, wherein said step of processing includes:

detecting breathing sound events by sound analysis in time and frequency domains; and

correlating said breathing sound events with direction, speed, timing and duration of concurrent body motions detected by said motion detector.

15. The method according to claim 10, further comprising performing frequency analysis measuring power distribution in said breathing sounds using a bi-level image of the breathing sounds spectrogram and an FFT of the image to detect repeating patterns.

16. The method according to claim 15, wherein a cough or wheeze sound is detected by comparing the spectrogram FFT results to predefined thresholds

17. A device for monitoring and analyzing breathing sounds, the device comprising:

at least one microphone, for contactless placement adjacent a body to be monitored, recording breathing sounds from said body;

a motion detector, including an ultrasonic distance sensor, to detect motions of said body;

a processor, implementing time domain analysis and frequency domain analysis of said recorded breathing sounds, coupled to said microphones and said motion detector for receiving and processing said breathing sounds and concurrent detected motions to detect abnormal breath events.