Methods for Non-Invasively Monitoring Health

• US 20100317979A1
• Filed: 08/23/2010
• Published: 12/16/2010
• Est. Priority Date: 10/17/2002
• Status: Active Grant

• Current Assignee: Craig A. Kelly
• Original Assignee: Craig A. Kelly
• Inventors: Kelly, Craig A.
• Granted Patent: US 7,927,277 B2
• Time in Patent Office: Days
• US Class Current: 600/508
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: A61B 5/7257 using Fourier transforms

Abstract

The time between heartbeats is measured over a series of such heartbeats. The time interval between two successive events is calculated and stored as a first array. The time difference between adjacent heartbeat intervals is also calculated from the first array and recorded as a differential array. The differential array is subjected to frequency analysis. First the differential array data is linearly interpolated to increase the number of data samples. The interpolated data is then subjected to a fast fourier transform (FFT) yielding a power spectrum. Characteristic frequency ranges are then integrated and the resulting frequency domain spectrum(s) are analyzed for dominant frequency characteristics.

Claims

1. A method of monitoring health non-invasively comprising:

creating a first array of data based on discretely recorded time events in which each element of the first array is representative of a time when an event took place;

creating a second array of data in which each element of the second array is an interval representative of the difference between successive elements of the first array;

creating a third array of data in which each element of the third array is a delta interval representative of the difference between successive elements of the second array;

performing a fast fourier transform (FFT) on the third array to obtain power spectrum data representative of the third array; and

integrating the power spectrum data over frequency ranges of interest to obtain discrete power values for said frequency ranges of interest.

2. A method of monitoring health non-invasively to assist in cardiac evaluation comprising:

creating a first array of heart vibrations based on discretely recorded heartbeats in which each element of the first array is representative of a time when a heartbeat took place;

creating a heart period array in which each element is a heart period interval representative of the difference between successive elements of the first array of heart vibrations;

creating a delta heart period interval array in which each element is a delta heart period interval representative of the difference between successive elements of the heart period interval array;

performing a fast fourier transform (FFT) on the delta heart period interval array to obtain power spectrum data representative of the delta heart period interval array; and

integrating the power spectrum data over one or more frequency ranges of interest to obtain discrete power values for said one or more frequency ranges of interest.

3. The method of claim 2 wherein the frequency ranges of interest include a low frequency (LF) range, a high frequency (HF) range, and a very high frequency (VHF) range.

4. The method of claim 3 further comprising:

calculating a total power, TP, value that is the sum of the LF, HF, and VHF power values.

5. The method of claim 3 further comprising:

calculating a power ratio value that is equal to LF/HF.

6. The method of claim 4 further comprising:

calculating a normalized LF power value that is equal to LF/TP.

7. The method of claim 4 further comprising:

calculating a normalized HF power value that is equal to HF/TP.

8. The method of claim 4 further comprising:

calculating a normalized VHF power value that is equal to VHF/TP.

9. The method claim 3 wherein the LF range is approximately 0.04 to 0.15 Hz.

10. The method of claim 3 wherein the HF range is approximately 0.15 to 0.4 Hz.

11. The method of claim 3 wherein the VHF range is approximately 0.4 to 1.0 Hz.

12. A method of monitoring health non-invasively to assist in respiration evaluation comprising:

creating a first array of respiration events based on discretely recorded body motions in which each element of the first array is representative of a time when a respiration event took place;

creating a respiration period interval array in which each element is a respiration period interval representative of the difference between successive elements of the first array of respiration events;

creating a delta respiration period interval array in which each element is a delta respiration period interval representative of the difference between successive elements of the respiration period interval array;

performing a fast fourier transform (FFT) on the delta respiration period interval array to obtain power spectrum data representative of the delta respiration period interval array; and

integrating the power spectrum data over a low frequency (LF) range of interest to obtain a discrete power value.

13. The method of claim 12 wherein the LF range is approximately 0.04 to 0.3 Hz.

14. A method of monitoring health non-invasively to assist in cardiac evaluation comprising:

creating a first array of heart vibrations based on discretely recorded heartbeats in which each element of the first array is representative of a time when a ventricular heart vibration of a heartbeat took place;

creating a second array of heart vibrations having an element to element association with the first array of heart vibrations, said second array of heart vibrations representative of a time when a systolic heart vibration of a heartbeat took place;

creating a ventricular systole interval array in which each element is an interval representative of the time difference between the second and first heart vibrations of each heartbeat in the second and first arrays;

creating a delta ventricular systole interval array in which each element is a delta ventricular systole interval representative of the difference between successive elements of the ventricular systole interval array;

performing a fast fourier transform (FFT) on the delta ventricular systole interval array to obtain power spectrum data representative of the delta ventricular systole interval array; and

integrating the power spectrum data over one or more frequency ranges of interest to obtain discrete power values for said one or more frequency ranges of interest.

15. The method of claim 14 wherein the frequency ranges of interest include a low frequency (LF) range, a high frequency (HF) range, and a very high frequency (VHF) range.

16. The method of claim 15 further comprising:

calculating a total power, TP, value that is the sum of the LF, HF, and VHF power values.

17. The method of claim 15 further comprising:

calculating a power ratio value that is equal to LF/HF.

18. The method of claim 16 further comprising:

calculating a normalized LF power value that is equal to LF/TP.

19. The method of claim 16 further comprising:

calculating a normalized HF power value that is equal to HF/TP.

20. The method of claim 16 further comprising:

calculating a normalized VHF power value that is equal to VHF/TP.

21. The method of claim 15 wherein the LF range is approximately 0.04 to 0.15 Hz.

22. The method of claim 15 wherein the HF range is approximately 0.15 to 0.4 Hz.

23. The method of claim 15 wherein the VHF range is approximately 0.4 to 1.0 Hz.

24. A method of monitoring health non-invasively comprising:

creating a first array of data based on discretely recorded time events in which each element of the first array is representative of a time when an event took place;

creating a second array of data in which each element of the second array is an interval representative of the difference between successive elements of the first array;

creating a third array of data in which each element of the third array is a delta interval representative of the difference between non-successive elements of the second array;

performing a fast fourier transform (FFT) on the third array of data to obtain power spectrum data representative of the third array of data; and

integrating the power spectrum data over frequency ranges of interest to obtain discrete power values for said frequency ranges of interest.