BREATHING DISORDER IDENTIFICATION, CHARACTERIZATION AND DIAGNOSIS METHODS, DEVICES AND SYSTEMS

• US 20140188006A1
• Filed: 05/17/2012
• Published: 07/03/2014
• Est. Priority Date: 05/17/2011
• Status: Active Grant

• Current Assignee: University Health Network
• Original Assignee: University Health Network
• Inventors: Alshaer, Hisham, Fernie, Geoffrey Roy, Bradley, T. Douglas, Akl, Ahmad Ziad
• Granted Patent: US 9,801,590 B2
• Time in Patent Office: Days
• US Class Current: 600/586
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/6803 Head-worn items, e.g. helmets, masks, headphones or goggles
• 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 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A61B 7/003 Detecting lung or respiration noise

Abstract

Disclosed herein are breathing disorder identification, characterization and diagnosis methods, devices and systems. In general the disclosed methods, devices and systems may rely on the characterization of breath sound amplitudes, periodic breath sounds and/or aperiodic breath sounds to characterize a breathing disorder as obstructive (e.g. obstructive sleep apnea - OSA) or non-obstructive (e.g. central sleep apnea—CSA).

Claims

1. A method for automatically characterizing recorded breath sounds as indicative of one of obstructive and central sleep apnea, the method comprising:

identifying a segment of the recorded breath sounds encompassing at least one of an apnea and a hypopnea;

automatically evaluating a breath sound amplitude profile of said identified segment against one or more preset sound amplitude profile criteria set to distinguish between segments indicative of obstructive sleep apnea and central sleep apnea; and

classifying said identified segment as being indicative of one of obstructive and central sleep apnea based on a result of said evaluating step.

2. The method of claim 1, said evaluating step further comprising:

characterizing a variation in said breath sound amplitude profile to output a characteristic representative thereof; and

evaluating said characteristic against said one or more criteria.

3. The method of claim 2, said segment comprising a falling edge and a rising edge separated by a low-amplitude segment associated, with said apnea or hypopnea, said characterizing step comprising characterizing a profile pattern at least partially defined by said falling edge and said rising edge, said one or more criteria predetermined as a function of such characteristic patterns previously associated with obstructive and central sleep apnea.

4. The method of claim 3, said profile pattern comprising a fall/rise pattern characterized as either a crescendo-decrescendo pattern indicative of central sleep apnea and a gradual fall-abrupt rise pattern indicative of obstructive sleep apnea.

5. The method of claim 2, said segment comprising a falling edge and a rising edge separated by a low-amplitude segment associated with said apnea or hypopnea, said characterizing step comprising evaluating a similarity between said rising edge and said falling edge, said one or more criteria comprising a similarity threshold set to distinguish obstructive from central apnea events.

6. The method of claim 5, said characteristic comprising a similarity index calculated by comparing said falling edge and said rising edge using a Dynamic Time Warping (DTW) subroutine.

7. The method of claim 1 further comprising repeating the steps for multiple segments.

9. The method of claim 1, further comprising the steps of:

automatically identifying inspiration and expiration phases of the recorded breath sounds;

isolating expiration breath sounds from said recorded sounds; and

extracting said breath sound amplitude profile from said isolated expiration sounds, whereby said segment is representative of expiration sounds only.

10. The method of claim 1, said step of identifying said segment further comprising:

scanning said extracted breath sound amplitude profile to identify a prospect event segment;

evaluating characteristics of said prospect event segment for consistency with at least one of;

one or more preset apnea-specific criteria, and one or more preset hypopnea-specific criteria distinct from said apnea-specific criteria; and

identifying said prospect event as encompassing an apnea or a hypopnea upon it satisfying each of said one or more apnea-specific criteria or each of said one or more preset hypopnea-specific criteria.

11. The method of claim 1, further comprising:

extracting one or more spectral characteristics associated with said identified segment; and

evaluating said extracted spectral characteristics against one or more corresponding classification criteria predetermined to distinguish obstructive breathing events from non-obstructive breathing events;

said classifying step comprising combining amplitude-related and spectrum-related evaluation results to classify said identified segment.

12. The method of claim 11, said one or more spectral characteristics associated with at least a respective one of periodic breath sounds and aperiodic breath sounds manifested in a period encompassing said identified segment.

43. The method of claim 1, further comprising the step of acquiring breath sounds via a face mask comprising a microphone disposed, upon a candidate wearing the mask during sleep, at a distance above a nose and mouth area of the candidate'"'"'s face.

44. The method of claim 1, automatically implemented by one or more processors of a computing system, and further comprising outputting, via a user interface, an indication of a candidate'"'"'s condition.

45. A computer-readable medium comprising statements and instructions stored thereon for implementation by one or more processors of a computing system to automatically characterize recorded breath sounds as indicative of one of obstructive and central sleep apnea, in accordance with the steps of the method as claimed in claim 1.

46. A system for automatically characterizing recorded breath sounds as indicative of one of obstructive and central sleep apnea, the system comprising:

one or more processors;

a computer-readable medium accessible by said one or more processors and having stored thereon statements and instructions executable thereby to operate on said recorded breath sounds in accordance with the method of claim 1.

47. The system of claim 46, further comprising a face mask having a microphone mounted thereon and reproducibly disposable, upon the candidate wearing the mask during sleep, at a distance above a nose and mouth area of the candidate so to intercept and capture airflow sounds emanating therefrom for processing.

48. The system of claim 47, said mask further comprising a removable data storage medium operatively coupled to said microphone for storing recorded breath sounds thereon prior to processing.

56. The computer-readable medium of claim 45, wherein said evaluating step further comprises:

characterizing a variation in said breath sound amplitude profile to output a characteristic representative thereof; and

evaluating said characteristic against said one or more criteria; and

wherein said segment comprises a falling edge and a rising edge separated by a low-amplitude segment associated with said apnea or hypopnea, said characterizing step comprising characterizing a profile pattern at least partially defined by said falling edge and said rising edge, said one or more criteria predetermined as a function of such characteristic patterns previously associated with obstructive and central sleep apnea.

57. The computer-readable medium of claim 56, said profile pattern comprising a fall/rise pattern characterized as either a crescendo-decrescendo pattern indicative of central sleep apnea and a gradual fall-abrupt rise pattern indicative of obstructive sleep apnea.

8. (canceled)

13-42. -42. (canceled)

49-55. -55. (canceled)

58. The computer readable medium of 56, wherein said evaluating step further comprises:

characterizing a variation in said breath sound amplitude profile to output a characteristic representative thereof; and

evaluating said characteristic against said one or more criteria; and

wherein said segment comprises a falling edge and a rising edge separated by a low-amplitude segment associated with said apnea or hypopnea, said characterizing step comprising evaluating a similarity between said rising edge and said falling edge, said one or more criteria comprising a similarity threshold set to distinguish obstructive from central apnea events.