Apparatus and method for predicting cardiac arrhythmia by detection of micropotentials and analysis of all ECG segments and intervals

• US 5,609,158 A
• Filed: 05/01/1995
• Issued: 03/11/1997
• Est. Priority Date: 05/01/1995
• Status: Expired due to Term

• Current Assignee: Arrhythmia Research Technology, Inc.
• Original Assignee: Arrhythmia Research Technology, Inc.
• Inventors: Chan, Eric K. Y.
• Primary Examiner(s): Jastrzab, Jeffrey R.
• Application Number:
  US08/431,992
• Time in Patent Office: 680 Days
• Field of Search: 128/696, 128/702-705, 364/413.05, 364/413.06
• US Class Current: 600/518
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/353 Detecting P-waves
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: A61B 5/7253 characterised by using transforms
• CPC Class Codes: A61B 5/7257 using Fourier transforms

Abstract

An apparatus and method for the acquisition and analysis of electrocardiogram signals, to non-invasively detect and quantify presence of abnormal cardiac conduction patterns in patients at risk of heart disease, e.g. ventricular tachycardia; atrial fibrillation and flutter. Signals from the orthogonal X, Y and Z surface leads are amplified, digitized and either stored for later processing, or processed immediately. The incoming beats can either be R wave-triggered, aligned and ensemble-averaged for studies of patients at risk for ventricular pathologies such as ventricular tachycardia, or P wave-triggered, aligned and ensemble-averaged for studies of patients at risk for atrial pathologies, e.g. atrial fibrillation and flutter. QRS onset and offset, and P wave onset and offset, are calculated for ventricular and atrial post-analysis applications, respectively. The windowed Fourier transform of the second derivative (acceleration) of the signal-averaged ECG is calculated for particular regions of interest for each lead, including the intra-QRS, ST-segment, T and P wave regions. A novel Spectral Change Index, calculated from the resulting "acceleration spectrum" for each lead as well as the composite (X+Y+Z) lead, serves to quantify the degree of spectral "fragmentation" within a prespecified bandwidth. It thereby provides a quantitative index to help stratify patients at risk for potentially lethal cardiac (atrial and ventricular) pathologies.

Claims

1. A method for detecting micropotentials to identify cardiac arrhythmia comprising the steps of:

selecting a segment of interest of an electrocardiographic signal of one cardiac cycle;

generating a profile waveform representative of a temporal attribute of said segment of interest;

deriving a frequency domain spectral representation of said profile waveform, said frequency domain representation being representative of said segment of interest with high frequency micropotentials being amplified therein;

defining a bandwidth of interest of frequencies in said spectral representation;

determining a gradient from said spectral representation for each of a plurality of the frequencies within said bandwidth of interest;

obtaining a representative maximum amplitude of said spectral representation for the frequencies within said bandwidth of interest;

comparing said representative maximum amplitude and said gradients from said spectral representation for each of the plurality of the frequencies to detect the micropotentials in the segment of interest of the electrocardiographic signal; and

quantifying a degree of spectral fragmentation within said bandwidth of interest from said comparing of said representative maximum amplitude and said gradients to identify cardiac arrhythmia.

2. A method in accordance with claim 1 wherein said selecting step comprises signal averaging of a plurality of cardiac cycles to reduce the noise level in a representative waveform.

3. A method in accordance with claim 2 wherein said generating step further comprises a step of taking a second derivative of said segment of interest of the electrocardiographic signal as said profile waveform representative of the temporal attribute.

4. A method in accordance with claim 3 wherein said deriving step further comprises the step of windowing said profile waveform in performing a frequency domain transformation using a Fourier transform.

5. A method in accordance with claim 4 wherein said defining step defines said bandwidth of interest as being about 50 Hz to about 300 Hz.

6. A method in accordance with claim 4 wherein said determining step comprises determining a gradient from said spectral representations for each of a plurality of the frequencies within said bandwidth of interest.

7. A method in accordance with claim 4 wherein said determining step comprises summing the absolute value of said gradients of said spectral representation within said bandwidth of interest.

8. A method in accordance with claim 4 wherein said obtaining step comprises identifying a plurality of spectral peaks from said spectral representation for the frequencies within said bandwidth of interest and discerning said representative maximum amplitude of said spectral representation as being the largest spectral peak identified.

9. A method in accordance with claim 7 wherein said comparing step comprises dividing the sum, determined in said determining step of summing the absolute value of said gradients of said spectral representation, by said representative maximum amplitude to compute an index quantifying the degree of spectral fragmentation within said bandwidth of interest.

10. A method for detecting micropotentials to identify cardiac arrhythmia comprising the steps of:

selecting a segment of interest of an electrocardiographic signal of one cardiac cycle;

generating a profile waveform representative of a temporal attribute of said segment of interest;

deriving a frequency domain spectral representation of said profile waveform, said frequency domain representation being representative of said segment of interest with high frequency micropotentials being amplified therein;

defining a bandwidth of interest of frequencies in said spectral representation;

characterizing a degree of variation within said bandwidth of interest of frequencies in said spectral representation to detect the micropotentials in the segment of interest of the electrocardiographic signal; and

said characterizing step quantifying a degree of spectral fragmentation within said bandwidth of interest to identify cardiac arrhythmia.

11. A method in accordance with claim 10 wherein said generating step further comprises a step of taking a second derivative of said segment of interest of the electrocardiographic signal as said profile waveform representative of the temporal attribute.

12. A method in accordance with claim 11 wherein said characterizing step counts said spectral peaks to detect the micropotentials included in the frequency domain from about 50 Hz to about 300 Hz in the electrocardiographic signal to quantify the degree of spectral fragmentation therein.

13. A method in accordance with claim 10 wherein said characterizing step comprises the steps of:

identifying a plurality of spectral peaks from said spectral representation for the frequencies within said bandwidth of interest; and

counting said spectral peaks to detect the micropotentials in the segment of interest of the electrocardiographic signal to quantify the degree of spectral fragmentation within said bandwidth of interest.

14. A method in accordance with claim 13 wherein said defining step defines said bandwidth of interest as being about 50 Hz to about 300 Hz.

15. An apparatus for detecting micropotentials to identify cardiac arrhythmia comprising:

a computer;

a signal storage device addressable by said computer;

a signal acquisition module operable with said computer to select a segment of interest of an electrocardiographic signal of one cardiac cycle, to save said segment of interest in said signal storage device and to generate a profile waveform representative of a temporal attribute of said segment of interest;

a frequency domain transformation program utilized by said computer to derive a spectral representation of said profile waveform representative of said segment of interest with high frequency micropotentials being amplified within a bandwidth of interest for characterizing a degree of variation within said spectral representation to detect the micropotentials in said segment of interest of the electrocardiographic signal; and

said frequency domain transformation program quantifying a degree of spectral fragmentation within said bandwidth of interest to identify cardiac arrhythmia.

16. An apparatus in accordance with claim 15 wherein said frequency domain transformation program utilized by said computer comprises:

means for determining a gradient from said spectral representation for each of a plurality of the frequencies within said bandwidth of interest;

means for obtaining a representative maximum amplitude of said spectral representation for the frequencies within said bandwidth of interest; and

means for comparing said representative maximum amplitude and said gradients from said spectral representation for each of the plurality of the frequencies to detect the micropotentials in the segment of interest of the electrocardiographic signal to quantify the degree of spectral fragmentation within said bandwidth of interest.

17. An apparatus in accordance with claim 15 wherein said signal acquisition module operable with said computer comprises means for taking the second derivative of said segment of interest of the electrocardiographic signal as said profile waveform representative of the temporal attribute.

18. An apparatus in accordance with claim 16 wherein said comparing means comprises means for determining the absolute value of said gradients of said spectral representation, and summing said absolute value of said gradients within said bandwidth of interest, and dividing the sum of the absolute value of said gradients of said spectral representation by said representative maximum amplitude to compute an index quantifying the degree of spectral fragmentation within said bandwidth of interest.

19. An apparatus in accordance with claim 15 wherein said frequency domain transformation program utilized by said computer comprises means for characterizing the degree of variation within said bandwidth of interest of frequencies in said spectral representation to detect the micropotentials in the segment of interest of the electrocardiographic signal to quantify the degree of spectral fragmentation within said bandwidth of interest.

20. An apparatus in accordance with claim 19 wherein said means for characterizing comprises:

means for identifying a plurality of spectral peaks from said spectral representation for the frequencies within said bandwidth of interest; and

means for counting said spectral peaks to detect the micropotentials in the segment of interest of the electrocardiographic signal to quantify the degree of spectral fragmentation within said bandwidth of interest.

21. A method for detecting micropotentials to identify cardiac arrhythmia comprising the steps of:

selecting a segment of interest of an electrocardiographic signal of one cardiac cycle;

generating a profile waveform representative of a temporal attribute of said segment of interest;

deriving a frequency domain spectral representation of said profile waveform, said frequency domain representation being representative of said segment of interest with high frequency micropotentials being amplified therein;

defining a bandwidth of interest of frequencies in said spectral representation;

determining a gradient from said spectral representation for each of a plurality of the frequencies within said bandwidth of interest;

obtaining a representative spectral change index for the frequencies within said bandwidth of interest;

comparing said representative spectral change index and said gradients from said spectral representation for each of the plurality of the frequencies to detect the micropotentials in the segment of interest of the electrocardiographic signal; and

quantifying a degree of spectral fragmentation within said bandwidth of interest from said comparing of said representative spectral change index and said gradients to identify cardiac arrhythmia.

22. A method in accordance with claim 21 wherein said selecting step comprises signal averaging of a plurality of cardiac cycles to reduce the noise level in a representative waveform.

23. A method in accordance with claim 22 wherein said generating step further comprises a step of taking a second derivative of said segment of interest of the electrocardiographic signal as said profile waveform representative of the temporal attribute.

24. A method in accordance with claim 23 wherein said deriving step further comprises the step of windowing said profile waveform in performing a frequency domain transformation using a Fourier transform.

25. A method in accordance with claim 24 wherein said defining step defines said bandwidth of interest as being about 50 Hz to about 300 Hz.

26. A method in accordance with claim 24 wherein said determining step comprises determining a gradient from said spectral representations for each of a plurality of the frequencies within said bandwidth of interest.

27. A method in accordance with claim 24 wherein said determining step comprises summing the absolute value of said gradients of said spectral representation within said bandwidth of interest.