Assessment of sleep quality and sleep disordered breathing based on cardiopulmonary coupling

• US 20050256418A1
• Filed: 05/17/2004
• Published: 11/17/2005
• Est. Priority Date: 05/17/2004
• Status: Active Grant

• Current Assignee: BETH Israel Deaconess Medical Center (Caregroup Incorporated)
• Original Assignee: BETH Israel Deaconess Medical Center (Caregroup Incorporated)
• Inventors: Peng, Chung-Kang, Goldberger, Ary L., Thomas, Robert J., Mietus, Joseph E.
• Granted Patent: US 7,324,845 B2
• Time in Patent Office: Days
• US Class Current: 600/512
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/372 Analysis of electroencephalograms
• CPC Class Codes: A61B 5/398 Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG]
• CPC Class Codes: A61B 5/4815 Sleep quality
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence

Abstract

An assessment of sleep quality and sleep disordered breathing is determined from the cardiopulmonary coupling between two physiological data series. In an embodiment, an R-R interval series is derived from an electrocardiogram (ECG) signal. The normal beats from the R-R interval series are extracted to produce a normal-to-normal (NN) interval series. The amplitude variations in the QRS complex are used to extract to a surrogate respiration signal (i.e., ECG-derived respiration (EDR)) that is associated with the NN interval series. The two series are corrected to remove outliers, and resampled. The cross-spectral power and coherence of the two resampled signals are calculated over a plurality of coherence windows. For each coherence window, the product of the coherence and cross-spectral power is used to calculate coherent cross power. Using the appropriate thresholds for the coherent cross power, the proportion of sleep spent in CAP, non-CAP, and wake and/or REM are determined.

Claims

1. A method of detecting cardiopulmonary coupling between heart rate variability and respiration of a subject, comprising:

accessing a first series of physiological data representing respiration dynamics of the subject;

accessing a second series of physiological data representing heart rate dynamics of the subject, said second series being temporally aligned with said first series; and

detecting cardiopulmonary coupling between said first series and said second series.

2. The method according to claim 1, further comprising:

comparing said cardiopulmonary coupling with a detection threshold for determining cyclic alternating pattern (CAP) activity.

3. The method according to claim 1, further comprising:

comparing said cardiopulmonary coupling with a detection threshold for determining non-CAP activity.

4. The method according to claim 1, further comprising:

comparing said cardiopulmonary coupling with a detection threshold for determining wake and/or REM activity.

5. The method according to claim 1, further comprising:

comparing said cardiopulmonary coupling with a detection threshold for determining a sleep breathing disorder.

6. The method according to claim 1, further comprising:

accessing a single set of physiological data, said single set of physiological data being the source for said accessing of said first series and said accessing of said second series.

7. The method according to claim 6, further comprising:

accessing electrocardiogram data as said single set of physiological data.

8. The method according to claim 7, wherein said accessing a second series comprises:

extracting a series of normal-to-normal heart beats from said electrocardiogram data to access said second series.

9. The method according to claim 7, wherein said accessing a first series comprises:

extracting a series of QRS amplitude data from said electrocardiogram data to access said first series.

10. The method according to claim 1, wherein said detecting comprises:

determining a cross-spectra power and a coherence for each of a plurality of temporally aligned subsets of data from said first series and said second series; and

computing a coherent cross power for each temporally aligned subset, said coherent cross power being computed from the product of said cross-spectra power and said coherence of each temporally aligned subset.

11. The method according to claim 10, wherein said detecting further comprises:

evaluating said coherent cross power for each temporally aligned subset to detect said cardiopulmonary coupling between said first series and said second series.

12. A computer program product comprising a computer useable medium having computer readable program code functions embedded in said medium for causing a computer to detect cardiopulmonary coupling between heart rate variability and respiration of a subject, comprising:

a first computer readable program code function that causes the computer to access a first series of physiological data representing respiration dynamics of the subject;

a second computer readable program code function that causes the computer to access a second series of physiological data representing heart rate dynamics of the subject, said second series being temporally aligned with said first series; and

a third computer readable program code function that causes the computer to detect cardiopulmonary coupling between said first series and said second series.

13. The computer program product according to claim 12, further comprising:

a fourth computer readable program code function that causes the computer to compare said cardiopulmonary coupling with a detection threshold for determining CAP activity.

14. The computer program product according to claim 12, further comprising:

a fourth computer readable program code function that causes the computer to compare said cardiopulmonary coupling with a detection threshold for determining non-CAP activity.

15. The computer program product according to claim 12, further comprising:

a fourth computer readable program code function that causes the computer to compare said cardiopulmonary coupling with a detection threshold for determining wake and/or REM activity.

16. The computer program product according to claim 12, further comprising:

a fourth computer readable program code function that causes the computer to compare said cardiopulmonary coupling with a detection threshold for determining a sleep breathing disorder.

17. The computer program product according to claim 12, further comprising:

a fourth computer readable program code function that causes the computer to access a single set of physiological data, said single set of physiological data being the source for said accessing of said first series and said accessing of said second series.

18. The computer program product according to claim 17, further comprising:

a fifth computer readable program code function that causes the computer to access electrocardiogram data as said single set of physiological data.

19. The computer program product according to claim 12, wherein said third computer readable program code function comprises:

a fourth computer readable program code function that causes the computer to determine a cross-spectra power and a coherence for each of a plurality of temporally aligned subsets of data from said first series and said second series; and

a fifth computer readable program code function that causes the computer to compute a coherent cross power for each temporally aligned subset, said coherent cross power being computed from the product of said cross-spectra power and said coherence of each temporally aligned subset.

20. The computer program product according to claim 19, wherein said third computer readable program code function further comprises:

a sixth computer readable program code function that causes the computer to evaluate said coherent cross power for each temporally aligned subset to detect said cardiopulmonary coupling between said first series and said second series.