Methods for non-invasively monitoring health

• US 7,927,277 B2
• Filed: 08/23/2010
• Issued: 04/19/2011
• Est. Priority Date: 10/17/2002
• Status: Expired due to Fees

• Current Assignee: Johns Hopkins University
• Original Assignee: Johns Hopkins University
• Inventors: Kelly, Craig A.
• Primary Examiner(s): Casler; Brian
• Assistant Examiner(s): Kish; James
• Application Number:
  US12/861,440
• Publication Number:
  US 20100317979A1
• Time in Patent Office: 239 Days
• Field of Search: 600/437, 600/438, 600/450, 600/500, 607/17
• US Class Current: 600/437
• 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 by physiological monitoring of body motion using a non-invasive sensor comprising:

creating a first array of data using a processor based on discretely recorded body motion events detected by the sensor in which each element of the first array is representative of a time when a body motion event took place;

creating a second array of data using a processor 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 using a processor 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 using a processor to obtain power spectrum data representative of the third array;

integrating the power spectrum data over frequency ranges of interest using a processor to obtain discrete power values for said frequency ranges of interest; and

displaying the power spectrum data and discrete power values using a display device to monitor health.

2. A method of monitoring health by physiological monitoring of body motion using a non-invasive sensor to assist in cardiac evaluation comprising:

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

creating a heart period array using a processor 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 using a processor 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 using a processor to obtain power spectrum data representative of the delta heart period interval array;

integrating the power spectrum data over one or more frequency ranges of interest using a processor to obtain discrete power values for said one or more frequency ranges of interest; and

displaying the power spectrum data and discrete power values using a display device to evaluate cardiac health.

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

6. The method of claim 4 further comprising:

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

7. The method of claim 4 further comprising:

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

8. The method of claim 4 further comprising:

calculating and displaying 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 by physiological monitoring of body motion using a non-invasive sensor to assist in respiration evaluation comprising:

creating a first array of respiration events using a processor based on discretely recorded body motions detected by the sensor 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 using a processor 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 using a processor 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 using a processor to obtain power spectrum data representative of the delta respiration period interval array;

integrating the power spectrum data over a low frequency (LF) range of interest using a processor to obtain a discrete power value; and

displaying the power spectrum data and discrete power value using a display device to evaluate respiration.

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

14. A method of monitoring health by physiological monitoring of body motion using a non-invasive sensor to assist in cardiac evaluation comprising:

creating a first array of heart vibrations using a processor based on discretely recorded heartbeats detected by the sensor 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 using a processor 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 using a processor 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 using a processor 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 using a processor to obtain power spectrum data representative of the delta ventricular systole interval array;

integrating the power spectrum data over one or more frequency ranges of interest using a processor to obtain discrete power values for said one or more frequency ranges of interest; and

displaying the power spectrum data and discrete power values using a display device to evaluate cardiac health.

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

18. The method of claim 16 further comprising:

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

19. The method of claim 16 further comprising:

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

20. The method of claim 16 further comprising:

calculating and displaying 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 by physiological monitoring of body motion using a non-invasive sensor comprising:

creating a first array of data using a processor based on discretely recorded body motion events detected by the sensor in which each element of the first array is representative of a time when a body motion event took place;

creating a second array of data using a processor 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 using a processor 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 using a processor to obtain power spectrum data representative of the third array of data;

integrating the power spectrum data over frequency ranges of interest using a processor to obtain discrete power values for said frequency ranges of interest; and

displaying the power spectrum data and discrete power values using a display device to monitor health.