DETECTION OF SLEEP APNEA USING RESPIRATORY SIGNALS

• US 20140200474A1
• Filed: 01/15/2014
• Published: 07/17/2014
• Est. Priority Date: 01/16/2013
• Status: Active Grant

• Current Assignee: Vital Connect, Inc.
• Original Assignee: Vital Connect, Inc.
• Inventors: NARASIMHAN, Ravi, SELVARAJ, Nandakumar
• Granted Patent: US 10,194,834 B2
• Time in Patent Office: Days
• US Class Current: 600/529
• CPC Class Codes: A61B 5/0806 by whole-body plethysmography measuring blood flow using plethysmography A61B5/0295; impedance plethysmography A61B5/053; measuring volume of the body or parts thereof A61B5/1073
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/087 Measuring breath flow
• CPC Class Codes: A61B 5/0878 using temperature sensing means
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00

Abstract

A method and system for sleep apnea detection are disclosed. The method comprises detecting at least one respiratory signal and utilizing a detection algorithm to automatically detect at least one sleep apnea event from the at least one respiratory signal. The system includes a sensor to determine at least one respiratory signal, a processor coupled to the sensor, and a memory device coupled to the processor, wherein the memory device includes a detection algorithm and an application that, when executed by the processor, causes the processor to utilize the detection algorithm to automatically determine at least one sleep apnea event from the at least one respiratory signal.

Claims

1. A method for sleep apnea detection, the method comprising:

detecting at least one respiratory signal; and

utilizing a detection algorithm to automatically determine at least one sleep apnea event from the at least one respiratory signal.

2. The method of claim 1, wherein the at least one respiratory signal is any of a nasal airflow respiratory (NAR) signal, a respiratory inductive plethysomography (RIP) effort signal and electrocardiogram (ECG) derived respiratory signal.

3. The method of claim 1, wherein the utilizing further comprises:

extracting a plurality of features from the at least one respiratory signal;

determining at least one candidate sleep apnea event using the plurality of features; and

confirming the at least one sleep apnea event using the at least one determined candidate sleep apnea event.

4. The method of claim 1, further comprising:

preprocessing of the at least one detected respiratory signal using a plurality of low-pass filters that are elliptic.

5. The method of claim 1, further comprising:

reducing at least one false positive from the at least one determined candidate sleep apnea event.

6. The method of claim 3, wherein the plurality of features include any of a low-pass filtered envelope width, a trend mean of the low-pass filtered envelope width, and a statistical dispersion of the low-pass filtered envelope width.

7. The method of claim 6, wherein the statistical dispersion of the low-pass filtered envelope width is a difference between 90^th and 10^th percentiles over a predetermined time period.

8. The method of claim 3, wherein the determining further comprises:

determining whether an instantaneous amplitude of a low-pass filtered envelope width of the at least one respiratory signal is less than an amplitude threshold times a trend mean of the low-pass filtered envelope width; and

determining whether the trend mean of the low-pass filtered envelope width is less than a variable times a statistical dispersion of the low-pass filtered envelope width.

9. The method of claim 8, wherein a counter is incremented if the instantaneous amplitude of the low-pass filtered envelope width is less than the amplitude threshold times the trend mean and the trend mean is less than the variable times the statistical dispersion, further wherein the at least one candidate sleep apnea event is determined if the counter is greater than a threshold.

10. The method of claim 3, wherein the confirming further comprises:

confirming the at least one sleep apnea event if both a mean during an apnea event is less than a mean threshold times a mean during baseline and the mean during the apnea event is less than a variable times a mean dispersion metric.

11. A wireless sensor device for sleep apnea detection, the wireless sensor device comprising:

a sensor to detect at least one respiratory signal;

a processor coupled to the sensor; and

a memory device coupled to the processor, wherein the memory device includes a detection algorithm and an application that, when executed by the processor, causes the processor to;

utilize the detection algorithm to automatically determine at least one sleep apnea event from the at least one respiratory signal.

12. The wireless sensor device of claim 11, wherein the at least one respiratory signal is any of a nasal airflow respiratory (NAR) signal, a respiratory inductive plethysomography (RIP) effort signal and electrocardiogram (ECG) derived respiratory signal.

13. The wireless sensor device of claim 11, wherein to utilize further comprises to:

extract a plurality of features from the at least one respiratory signal;

determine at least one candidate sleep apnea event using the plurality of features; and

confirm the at least one sleep apnea event using the at least one determined candidate sleep apnea event.

14. The wireless sensor device of claim 11, wherein the application, when executed by the processor, further causes the processor to:

preprocess of the at least one detected respiratory signal using a plurality of low-pass filters that are elliptic.

15. The wireless sensor device of claim 11, wherein the application, when executed by the processor, further causes the processor to:

reduce at least one false positive from the at least one determined candidate sleep apnea event.

16. The wireless sensor device of claim 13, wherein the plurality of features include any of a low-pass filtered envelope width, a trend mean of the low-pass filtered envelope width, and a statistical dispersion of the low-pass filtered envelope width.

17. The wireless sensor device of claim 16, wherein the statistical dispersion of the low-pass filtered envelope width is a difference between 90^th and 10^th percentiles over a predetermined time period.

18. The wireless sensor device of claim 13, wherein to determine further comprises to:

determine whether an instantaneous amplitude of a low-pass filtered envelope width of the at least one respiratory signal is less than an amplitude threshold times a trend mean of the low-pass filtered envelope width; and

determine whether the trend mean of the low-pass filtered envelope width is less than a variable times a statistical dispersion of the low-pass filtered envelope width.

19. The wireless sensor device of claim 18, wherein the application, when executed by the processor, further causes the processor to:

increment a counter if the instantaneous amplitude of the low-pass filtered envelope width is less than the amplitude threshold times the trend mean and the trend mean is less than the variable times the statistical dispersion, wherein the at least one candidate sleep apnea event is determined if the counter is greater than a threshold.

20. The method of claim 13, wherein to confirm further comprises to:

confirm the at least one sleep apnea event if both a mean during an apnea event is less than a mean threshold times a mean during baseline and a mean during the apnea event is less than a variable times a mean dispersion metric.