AUTOMATIC AND AMBULATORY MONITORING OF CONGESTIVE HEART FAILURE PATIENTS

• US 20080045815A1
• Filed: 06/18/2007
• Published: 02/21/2008
• Est. Priority Date: 06/20/2006
• Status: Active Grant

• Current Assignee: Adidas AG
• Original Assignee: Adidas AG
• Inventors: Derchak, P., Lucia, Gary, Myers, Lance
• Granted Patent: US 8,475,387 B2
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• 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 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/7257 using Fourier transforms

Abstract

This invention provides methods for non-invasively monitoring patients with congestive heart failure (CHF) and for reporting and/or warning of changes in the patients'"'"' status. The methods gather physiological data and combine the data into parameters by which the severity of CHF can be judged. Preferred parameters include periodic breathing and heart rate variability. This invention also provides systems for carrying out these methods which permit patients to engage in their normal daily activities. Preferably, physiological data analysis is performed by a portable electronic unit carried by the patients.

Claims

1. A method for automatically monitoring congestive heart failure (CHF) in a subject comprising:

receiving signals generated by non-invasively monitoring respiratory and cardiac physiology of the subject, the signals conveying information concerning at least the subject'"'"'s breath rate and volume and the subject'"'"'s cardiac rate;

examining the received signals for indications of periodic breathing (PB);

examining the received signals for indications of reduced heart rate variability (HRV); and

indicating the status of CHF in the subject in dependence on the indications of PB and on the indications of HRV.

2. The method of claim 1 wherein at least a portion of the signals are received when the subject is ambulatory.

3. The method of claim 1 wherein CHF is indicated to be of increased severity if indications of PB are found or if indications of reduced HRV are found.

4. The method of claim 1 wherein the received signals also convey information concerning the magnitude of the subject'"'"'s cardiac pulsations;

wherein the received signals are examined for indications of cardiac output (CO); and

wherein CHF is indicated to be of increased severity if indications of PB are found, or if indications of reduced HRV are found, or if indications of reduced CO are found.

5. The method of claim 1 wherein the received signals also convey information concerning the subject'"'"'s blood oxygen content (spO2);

and wherein CHF is indicated to be of increased severity if indications of reduced spO2 are found, or if, in case indications of reduced spO2 are absent, if PB is found.

6. A system for automatically monitoring of congestive heart failure (CHF) in a subject

a wearable item having non-invasive sensors that monitor respiratory and cardiac physiology of the subject and provide signals conveying information concerning at least the subject'"'"'s breath rate and volume and the subject'"'"'s cardiac rate;

a computing device operatively coupled to the sensors for

examining the sensor signals for indications of periodic breathing (PB);

examining the sensor signals for indications of reduced heart rate variability (HRV); and

indicating the status of CHF in the subject in dependence on the indications of PB and on the indications of HRV.

7. The system of claim 6 wherein the garment is sized and configured as a portion of a shirt or as one or more bands.

8. The system of claim 6 wherein the computing device has a size and configuration similar to that of a portable digital assistant.

9. The system of claim 6 wherein the system is sized and configured to be unobtrusively worn and/or carried by an ambulatory subject.

10. The system of claim 6 wherein the non-invasive sensors comprise one or more of an electrode sensor sensitive to electrocardiogram (ECG) signals or an inductive plethysmographic sensor sensitive to a time-varying size of a subject.

11. The system of claim 6 wherein the non-invasive sensors comprise one or more sensors sensitive to the time-varying sizes of a subject'"'"'s thorax (RC) or of a subject'"'"'s abdomen (AB) of the subject, and wherein the computing device determines a time-varying lung volume signal in dependence on the RC and/or the AB signals.

12. The system of claim 6 wherein the provided sensor signals include one or more signals sensitive to time-varying pulsations of the subject'"'"'s heart (TCG), and wherein the computing device determines indications of cardiac output (CO) from the TCG signals and indicates the status of CHF further in dependence on the CO indications.

13. A method for automatically monitoring congestive heart failure (CHF) in a subject comprising:

receiving signals generated by non-invasively monitoring respiratory physiology of the subject, the signals conveying information concerning at least the subject'"'"'s breath rate and volume;

examining the received signals for indications of periodic breathing (PB);

indicating the status of CHF in the subject to be of increased severity if indications of PB are found.

14. The method of claim 13 further comprising determining from the received signals a minute ventilation (VE) signal sampled at a fixed sampling rate.

15. The method of claim 14 wherein the step of examining further comprises:

forming an auto-correlogram by auto-correlating the VE signal at a zero temporal shift and at a plurality of non-zero temporal shifts; and

examining the auto-correlogram for indications of PB, PB being indicated if the auto-correlogram comprises a significant maximum at a non-zero temporal shift adjacent to the central maximum at zero temporal shift.

16. The method of claim 14 wherein the step of examining further comprises:

forming a power spectrum by a Fourier transform method of the VE data, the VE data having been windowed; and

examining the power spectrum for indications of PB, PB being indicated if the power spectrum comprises a significant maximum at a frequency characteristic of PB.

17. The method of claim 14 wherein the step of examining further comprises:

forming a power spectrum by a Lomb-Scargle method of the VE data, the VE data having been windowed; and

examining the power spectrum for indications of PB, PB being indicated if the power spectrum comprises a significant maximum at a frequency characteristic of PB.

18. The method of claim 14 wherein the step of examining further comprises:

forming a power spectrum by a Burg method of the VE data, the VE data having been windowed; and

examining the power spectrum for indications of PB, PB being indicated if the power spectrum comprises a significant maximum at a frequency characteristic of PB.

19. The method of claim 13 wherein the received signals convey information concerning the time-varying sizes of one or both of the subject'"'"'s thorax (RC) and of the subject'"'"'s abdomen (AB), and

wherein the step of examining further comprises forming a power spectrum of the received signals by one or more of an autocorrelation method, a Fourier transform method, a Lomb-Scargle method, and a Burg method;

and

examining the power spectrum for indications of PB, PB being indicated if the power spectrum comprises two significant maxima, one at a frequency characteristic of PB and another at a frequency characteristic of respiration.

20. The method of claim 19 further comprising, prior to the step of forming a power spectrum, de-tending the received signals and rectifying the de-trended signals.

21. The method of claim 13 wherein the step of examining further comprises:

calculating a plurality of entropies of a plurality of additional signals, the plurality of additional signals being derived from the received signals by performing windowing followed by a plurality of degrees of coarse graining; and

examining the plurality of entropies for indications of PB by comparing entropies at lesser degrees of coarse graining with entropies at greater degrees of coarse graining.

22. The method of claim 21 wherein one or more of the entropies are calculated according to the sample entropy method.

23. A method for automatically monitoring congestive heart failure (CHF) in a subject comprising:

receiving signals generated by non-invasively monitoring cardiac physiology of the subject, the signals conveying information concerning at least the subject'"'"'s cardiac rate;

examining the received signals for indications of reduced heart rate variability (HRV); and

indicating the status of CHF in the subject to be of increased severity if indications of reduced HRV are found

24. The method of claim 23 wherein the received signals further monitor respiratory physiology of the subject and convey information concerning the subject'"'"'s breath rate and volume, and further comprising:

examining the received signals for indications of periodic breathing (PB); and

suspending examining the received signals for indications of reduced HRV during periods in which PB is detected.

25. The method of claim 23 wherein the received signals further monitor respiratory physiology of the subject and convey information concerning the subject'"'"'s breath rate and volume, and further comprising:

examining the received signals for periods of unusually increased respiratory variability; and

suspending examining the received signals for indications of reduced HRV during periods of unusually increased respiratory variability.

26. The method of claim 25 wherein the step of examining the received signals for periods of unusually increased respiratory variability further comprises:

identifying in an earlier window period and in a later window period the positions or values of signal maxima or minima;

determining whether or not the positions and values identified in the later window period differ significantly from those identified in the earlier window period; and

providing indication of unusually increased respiratory variability in the later window period if significant differences are determined.

27. The method of claim 26 wherein two values differ significantly if a difference of the two values exceeds a predetermined threshold.

28. The method of claim 26 wherein only one, but not both, of the signal maxima or the signal minima are identified and compared.

29. The method of claim 26 wherein only one, but not both, of the values or of the positions of the signal maxima and/or signal minima are identified and compared

30. The method of claim 26 wherein only the positions of signal maxima and/or minima are identified and compared.