Noninvasive method for identifying coronary artery disease utilizing electrocardiography derived data

• US 5,655,540 A
• Filed: 04/06/1995
• Issued: 08/12/1997
• Est. Priority Date: 04/06/1995
• Status: Expired due to Term

• Current Assignee: Ronald D. Seegobin
• Original Assignee: Ronald D. Seegobin
• Inventors: Seegobin, Ronald D.
• Primary Examiner(s): Kamm, William E.
• Application Number:
  US08/418,175
• Time in Patent Office: 859 Days
• Field of Search: 364/413.06, 128/702, 128/705
• US Class Current: 600/515
• CPC Class Codes: A61B 5/35 by template matching
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A method of analyzing empirically derived electrocardiograph (ECG) data which allows surprisingly accurate catagorization of subjects into various abnormal and normal classifications is disclosed. The presently preferred embodiment of the present invention applies an algorithm which compares root-mean-square (RMS) mean values derived from analysis of a representative composite of selected portions of a number of ECG PQRST waveforms obtained from (ECG) investigation of a subject, to similarly derived RMS mean and RMS standard deviation values present in a compiled data bank derived from (ECG) investigation of numerous normals, in each of a plurality of frequency range bands. A highly diagnostic numerical "Score" is calculated by addition of "Score" components found to be acceptable under certain mathematical criteria, and provided by the algorithm. Visually interpretable power spectral density plots supplement the method.

Claims

1. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom, said method comprising, in a functional sequence, performance of the steps of:

a. obtaining data from (ECG) cycle(s) from each of a multiplicity of members of a population of subjects who have been documented as normal subjects, in that they do not show risk factors for, or demonstrate detectable cardiac abnormality, by monitoring at least one lead(s) of an (ECG) system;

b. selecting some (ECG) cycle portion, and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s) by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for (ECG) cycle(s) obtained from each of a number of members of said multiplicity of members of a population of subjects who have been documented as normal subjects, each said calculated average selected (ECG) cycle portion data set being a composite data set of said selected (ECG) cycle portion for said population of normal subjects, for a monitored (ECG) system lead;

c. obtaining data from (ECG) cycle(s) from a subject, by monitoring at least one lead(s) of an (ECG) system, said (ECG) system lead(s) monitored being the same as the monitored (ECG) system lead(s) utilized in step a. to obtain data utilized in step b.;

d. selecting some (ECG) cycle portion, which is the same as that selected in step b., and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s) by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for (ECG) cycle(s) obtained from said subject, each said calculated average selected (ECG) cycle portion data set being a composite data set of said selected (ECG) cycle portion for said subject, for a monitored (ECG) system lead;

e. calculating corresponding representative parameter(s) from resulting composite data sets calculated in steps b. and d., for monitored (ECG) system lead(s), for, respectively, said normal subject population and said subject;

f. comparing subject to corresponding normal subject population representative parameter(s), and combining results thereof to arrive at a "score", the magnitude of which "score" results from difference(s) between magnitude(s) of corresponding normal subject population, and subject representative parameter(s), which "score" magnitude increases when said difference(s) in magnitude(s) between corresponding normal subject population, and subject, representative parameter(s) increase, the magnitude of which "score" provides an indication of the cardiac status of said subject, with a "score" near zero being indicative of a subject properly categorized as a cardiac normal in that the magnitude(s) of subject representative parameter(s) are generally more closely matched to the magnitude(s) of corresponding normal subject population representative parameter(s), and with a progressively higher "score" being indicative of a subject progressively more properly categorized as a cardiac abnormal in that the magnitude(s) of subject representative parameter(s) are generally progressively less closely matched to the magnitude(s) of corresponding normal subject population representative parameter(s).

2. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 1, which further comprises performance of the steps of calculating, and comparing ratio(s) of subject, to corresponding ratio(s) of normal subject population, representative parameters, and combining results thereof with those from comparing subject to corresponding normal subject population, representative parameter(s), in arriving at said "score", the magnitude of which "score" then further results from difference(s) between magnitude(s) of corresponding normal subject population and subject ratio(s) of representative parameters, which "score" magnitude increases when difference(s) in magnitude(s) between corresponding normal subject population, and subject, ratio(s) of representative parameters increase.

3. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 2, which further comprises performance of the step of applying a confidence level acceptance test to results of comparing specific ratio(s) of subject, to corresponding specific ratio(s) of normal subject population representative parameters prior to combining results thereof to arrive at a "score", said confidence level test comprising:

a. the step of determining mean and standard deviation acceptance parameters for specific ratio(s) of normal subject population representative parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said population of normal subjects was calculated;

b. the step of determining an acceptance parameter for each corresponding specific ratio of subject representative parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said subject was calculated; and

c. the step of accepting the results of comparing a specific ratio of subject representative parameters, to a corresponding specific ratio of representative parameters for said normal subject population, in arriving at said "score", only if said acceptance parameter for said specific ratio of said subject representative parameters is set off by at least one associated normal subject population acceptance standard deviation from the acceptance mean of said corresponding specific ratio of normal subject population representative parameters.

4. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 1, which further comprises performance of the step of applying a confidence level acceptance test to results of comparing specific subject, to corresponding specific normal subject population, representative parameter(s) prior to combining results thereof to arrive at a "score", said confidence level test comprising:

a. the step of determining mean and standard deviation acceptance parameters for specific normal subject population representative parameter(s) based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said population of normal subjects was calculated;

b. the step of determining an acceptance parameter for each corresponding specific subject representative parameter based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said subject was calculated; and

c. the step of accepting the results of comparing a specific subject representative parameter, to a corresponding specific normal subject population representative parameter, in arriving at said "score", only if the acceptance parameter for said specific subject representative parameter is set off by at least one associated normal subject population acceptance standard deviation from the acceptance mean of said corresponding specific normal subject population representative parameter.

5. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 1, which further comprises performance of the steps of:

a. providing at least one coordinate system selected from the group consisting of magnitude vs. time, and magnitude vs. frequency;

b. for an (ECG) cycle portion, performing calculations necessary to plot and display and plotting and displaying normal subject population and subject (ECG) data as a function of at least one parameter selected from the group consisting of time and frequency, to respectively provide as desired, visually interpretable plots of (ECG) magnitude and power spectral density data, observation of which provides an indication of the cardiac status of said subject; and

c. observing and interpreting the displayed plot(s).

6. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 1, in which the step of comparing subject, to normal subject population, representative parameter(s) and combining the results thereof to arrive at a "score", includes performance of the step of selecting parameters from the group consisting of root-mean-square mean and root-mean-square standard deviation as representative parameters.

7. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom, said method comprising, in a functional sequence, performance of the steps of:

a. obtaining data from (ECG) cycle(s) from each of a multiplicity of members of a population of subjects who have been documented as normal subjects, in that they do not show risk factors for, or demonstrate detectable cardiac abnormality, by monitoring at least one leads) of an (ECG) system;

b. selecting some (ECG) cycle portion, and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s) by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for (ECG) cycle(s) obtained from each of a number of members of said multiplicity of members of a population of subjects who have been documented as normal subjects, each said calculated average selected (ECG) cycle portion data set being a composite data set of said selected (ECG) cycle portion for said population of normal subjects, for a monitored (ECG) system lead;

c. obtaining data from (ECG) cycle(s) from a subject, by monitoring at least one lead(s) of an (ECG) system, said (ECG) system lead(s) monitored being the same as the monitored (ECG) system lead(s) utilized in step a. to obtain data utilized in step b.;

d. selecting some (ECG) cycle portion, which is the same as that selected in step b., and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s) by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for (ECG) cycle(s) obtained from said subject, each said calculated average selected (ECG) cycle portion data set being a composite data set of said selected (ECG) cycle portion for said subject, for a monitored (ECG) system lead;

e. calculating corresponding representative parameter(s) and corresponding ratio(s) involving representative parameters from resulting composite data sets calculated in steps b. and d., for monitored (ECG) system lead(s), for, respectively, said normal subject population and said subject;

f. comparing specific ratio(s) of subject to corresponding specific ratio(s) of normal subject population representative parameters, and combining results thereof to arrive at a "score", the magnitude of which "score" results from difference(s) between magnitude(s) of specific corresponding ratio(s) of normal subject population, and ratio(s) of subject representative parameters, which "score" magnitude increases when said difference(s) in magnitude(s) between specific ratio(s) of corresponding normal subject population, and specific ratio(s) of subject representative parameters increase, the magnitude of which "score" provides an indication of the cardiac status of said subject, with a "score" near zero being indicative of a subject properly categorized as a cardiac normal in that the magnitude(s) of ratio(s) of subject representative parameters are generally more closely matched to the magnitude(s) of corresponding ratio(s) of normal subject population representative parameters, and with a progressively higher "score" being indicative of a subject progressively more properly categorized as a cardiac abnormal in that the magnitude(s) of ratio(s) of subject representative parameters are generally progressively less closely matched to the magnitude(s) of ratio(s) of corresponding normal subject population representative parameters.

8. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 7, which further comprises performance of the step of applying a confidence level acceptance test to results of comparing ratio(s) of subject, to corresponding ratio(s) of normal subject population, representative parameters prior to combining results thereof to arrive at a "score", said confidence level test comprising:

a. the step of determining acceptance mean and standard deviation parameters for specific ratio(s) of normal subject population representative parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said population of normal subjects was calculated;

b. the step of determining an acceptance parameter for each corresponding specific ratio of subject representative parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said subject was calculated; and

c. the step of accepting the results of comparing a specific ratio of subject representative parameters, to a corresponding specific ratio of representative parameters for said normal subject population, in arriving at said "score", only if the acceptance parameter for said specific ratio of said subject representative parameters is set off by at least one associated normal subject population acceptance standard deviation from the acceptance mean of said corresponding specific ratio of normal subject population representative parameters.

9. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 7, which further comprises performance of the steps of:

a. providing at least one coordinate system selected from the group consisting of magnitude vs. time, and magnitude vs. frequency;

b. for an (ECG) cycle portion, performing calculations necessary to plot and display and plotting and displaying normal subject population and subject (ECG) data, as a function of at least one parameter selected from the group consisting of time and frequency, to respectively provide as desired, visually interpretable plots of (ECG) magnitude and power spectral density data, observation of which provides an indication of the cardiac status of said subject; and

c. observing and interpreting displayed plot(s).

10. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 7, in which the step of comparing specific ratio(s) of subject, to corresponding specific ratio(s) of normal subject population, representative parameter(s) and combining the results thereof to arrive at a "score", which "score" provides an indication of the presence or absence of cardiac abnormality in said subject, includes performance of the step of selecting parameters from the group consisting of root-mean-square mean and root-mean-square standard deviation as representative parameters.

11. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom, said method comprising, in a functional sequence, performance of the steps of:

a. obtaining data from (ECG) cycle(s) from each of a multiplicity of members of a population of subjects who have been documented as normal subjects, in that they do not show risk factors for, or demonstrate detectable cardiac abnormality, by monitoring at least one lead(s) of an (ECG) system;

b. selecting some (ECG) cycle portion and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s), by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for (ECG) cycle(s) obtained from each of a number of said multiplicity of members of a population of subjects who have been documented as normal subjects, and selecting a plurality of frequency bands and applying filtering techniques, to provide a plurality of data sets for each said at least one (ECG) system lead(s) monitored, each said data set being a composite data set of said selected (ECG) cycle portion for said population of normal subjects in a monitored lead and selected frequency band range;

c. obtaining data from (ECG) cycle(s) from a subject, by monitoring at least one lead(s) of an (ECG) system, said (ECG) system lead(s) monitored being the same as the monitored (ECG) system lead(s) utilized in step a. to obtain data utilized in step b.;

d. selecting some (ECG) cycle portion, said (ECG) cycle portion being the same as that selected in step b. for said normal subject population, and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s), by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for subject (ECG) cycle(s), and selecting a plurality of frequency bands, said selected frequency bands being the same as those selected in step b. for said normal subject population, and applying filtering techniques which are the same as those applied in step b. for said normal subject population, to provide a plurality of data sets for each said at least one monitored (ECG) system lead(s), each said data set being a composite data set of said selected (ECG) cycle portion for said subject in a monitored lead and selected frequency band range;

e. calculating corresponding representative parameter(s) from resulting composite data sets calculated in steps b. and d., in said selected frequency band ranges for monitored (ECG) system lead(s), for respectively, said normal subject population and said subject;

f. comparing specific subject to specific normal subject population corresponding representative parameter(s), and combining results thereof to arrive at a "score", the magnitude of which "score" results from difference(s) between magnitude(s) of corresponding normal subject population and subject representative parameter(s), which "score" magnitude increases when said difference(s) in magnitude(s) between corresponding normal subject population and subject representative parameter(s) increase, the magnitude of which "score" provides an indication of the cardiac status of said subject, with a "score" near zero being indicative of a subject properly categorized as a cardiac normal in that the magnitude(s) of subject representative parameter(s) are generally more closely matched to the magnitude(s) of corresponding normal subject population representative parameter(s), and with a progressively higher "score" being indicative of a subject progressively more properly categorized as a cardiac abnormal in that the magnitude(s) of subject representative parameter(s) are generally progressively less closely matched to the magnitude(s) of corresponding normal subject population representative parameter(s).

12. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 11, which further comprises performance of the step of applying a confidence level acceptance test to results of comparing specific subject, to corresponding specific normal subject population, representative parameters prior to combining results thereof to arrive at a "score", said confidence level test comprising:

a. the step of determining mean and standard deviation acceptance parameters for specific normal subject population representative parameter(s) based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said population of normal subjects was calculated;

b. the step of determining an acceptance parameter for each corresponding specific subject representative parameter based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said subject was calculated; and

c. the step of accepting the results of comparing a specific subject representative parameter to a corresponding specific normal subject population representative parameter, in arriving at said "score", only if the acceptance parameter for said specific subject representative parameter is set off by at least one associated normal population acceptance standard deviation from the acceptance mean of said corresponding specific normal subject population representative parameter.

13. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 11, which further comprises performance of the steps of:

a. providing at least one coordinate system selected from the group consisting of magnitude vs. time, and magnitude vs. frequency;

b. for an (ECG) cycle portion, performing calculations necessary to plot and display and plotting and displaying normal subject population and subject (ECG) data in at least one frequency band range, as a function of at least one parameter selected from the group consisting of time and frequency, to respectively provide as desired, visually interpretable plots of (ECG) magnitude and power spectral density data, observation of which provides an indication of the cardiac status of said subject; and

c. observing and interpreting displayed plot(s).

14. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 11, in which the step of comparing corresponding subject, to normal subject population, representative parameter(s) and combining the results thereof to arrive at a "score", includes performance of the step of selecting parameters from the group consisting of root-mean-square mean and root-mean-square standard deviation.

15. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom, said method comprising, in a functional sequence, performance of the steps of:

a. obtaining data from (ECG) cycle(s) from each of a multiplicity of members of a population of subjects who have been documented as normal subjects, in that they do not show risk factors for, or demonstrate detectable cardiac abnormality, by monitoring at least one lead(s) of an (ECG) system;

b. selecting some (ECG) cycle portion and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s), by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for (ECG) cycle(s) obtained from each of a number of said multiplicity of members of a population of subjects who have been documented as normal subjects, and selecting a plurality of frequency bands and applying filtering techniques, to provide a plurality of data sets for said at least one (ECG) system lead(s) monitored, each said data set being a composite data set of said selected (ECG) cycle portion for said population of normal subjects in a monitored lead and selected frequency band range;

c. obtaining data from (ECG) cycle(s) from a subject, by monitoring at least one lead(s) of an (ECG) system, said (ECG) system lead(s) monitored being the same as the monitored (ECG) system lead(s) utilized in step a. to obtain data utilized in step b.;

d. selecting some (ECG) cycle portion, said (ECG) cycle portion being the same as that selected in step b. for said normal subject population, and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s), by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for subject (ECG) cycle(s), and selecting a plurality of frequency bands, said selected frequency bands being the same as those selected in step b. for said normal subject population, and applying filtering techniques which are the same as those applied in step b. for said normal subject population, to provide a plurality of data sets for said at least one monitored (ECG) system lead(s), each said data set being a composite data set of said selected (ECG) cycle portion for said subject in a monitored lead and selected frequency band range;

e. calculating corresponding representative parameter(s) and corresponding ratio(s) involving representative parameters from resulting composite data sets calculated in steps b. and d., in said selected frequency band ranges for monitored (ECG) system lead(s), for respectively, said normal subject population and said subject;

f. comparing specific ratio(s) of subject to corresponding specific ratio(s) of normal subject population representative parameters, and combining results thereof to arrive at a "score", the magnitude of which "score" results from difference(s) between magnitude(s) of corresponding specific ratio(s) of normal subject population and specific ratio(s) of subject representative parameters, which "score" magnitude increases when said difference(s) in magnitude(s) between specific ratio(s) of corresponding normal subject population and subject representative parameters increase, the magnitude of which "score" provides an indication of the cardiac status of said subject, with a "score" near zero being indicative of a subject properly categorized as a cardiac normal in that the magnitude(s) Of ratio(s) of subject representative parameters are generally more closely matched to the magnitude(s) of corresponding ratio(s) of normal subject population representative parameters, and with a progressively higher "score" being indicative of a subject progressively more properly categorized as a cardiac abnormal in that the magnitude(s) of ratio(s) of subject representative parameters are generally progressively less closely matched to the magnitude(s) of ratio(s) of corresponding normal subject population representative parameters.

16. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 15, which further comprises performance of the step of applying a confidence level acceptance test to results of comparing specific ratio(s) of subject, to corresponding specific ratio(s) of normal subject population, representative parameters prior to combining results thereof to arrive at a "score", said confidence level test comprising:

a. the step of determining mean and standard deviation acceptance parameters for specific ratio(s) of normal subject population representative parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said population of normal subjects was calculated;

b. the step of determining an acceptance parameter for each corresponding specific ratio of subject representative parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said subject was calculated; and

c. the step of accepting the results of comparing a specific ratio of subject representative parameters, to a corresponding specific ratio of representative parameters for said normal subject population, in arriving at said "score", only if the acceptance parameter for said specific ratio of said subject representative parameters is set off by at least one associated normal subject population acceptance standard deviation from the acceptance mean of said specific ratio of normal subject population representative parameters.

17. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 15, which further comprises performance of the steps of:

a. providing at least one coordinate system selected from the group consisting of magnitude vs. time, and magnitude vs. frequency;

b. for an (ECG) cycle portion, performing calculations necessary to plot and display and plotting and displaying normal subject population and subject (ECG) data for at least one frequency band range, as a function of at least one parameter selected from the group consisting of time and frequency, to respectively provide as desired, visually interpretable plots of (ECG) magnitude and power spectral density data, observation of which provides an indication of the cardiac status of said subject; and

c. observing and interpreting displayed plot(s).

18. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 15, in which the step of comparing ratio(s) of subject, to corresponding ratio(s) of normal subject population, representative parameters and combining the results thereof to arrive at a "score", includes performance of the step of selecting ratios of parameter(s) from the group consisting of a ratio of a root-mean-square mean to at least one other root-mean-square mean, and a ratio of at least one root-mean-square mean to a root-mean-square standard deviation.

19. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom, said method comprising, in a functional sequence, performance of the steps of:

a. obtaining data from (ECG) cycle(s) from each of a multiplicity of members of a population of subjects who have been documented as normal subjects, in that they do not show risk factors for, or demonstrate detectable cardiac abnormality, by monitoring at least one lead(s) of an (ECG) system;

b. selecting some (ECG) cycle portion and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s), by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for (ECG) cycle(s) obtained from each of a number of said multiplicity of members of a population of subjects who have been documented as normal subjects, and selecting a plurality of frequency bands and applying filtering techniques, to provide a plurality of data sets for said at least one (ECG) system lead(s) monitored, each said data set being a composite data set of said selected (ECG) cycle portion for said population of normal subjects in a monitored lead and selected frequency band range;

c. obtaining data from (ECG) cycle(s) from a subject, by monitoring at least one lead(s) of an (ECG) system, said (ECG) system lead(s) monitored being the same as the monitored (ECG) system lead(s) utilized in step a. to obtain data utilized in step b.;

d. selecting some (ECG) cycle portion, said (ECG) cycle portion being the same as that selected in step b. for said normal subject population, and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s), by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for subject (ECG) cycle(s), and selecting a plurality of frequency bands, said selected frequency bands being the same as those selected in step b. for said normal subject population, and applying filtering techniques which are the same as those applied in step b. for said normal subject population, to provide a plurality of data sets for said at least one monitored (ECG) system lead(s), each said data set being a composite data set of said selected (ECG) cycle portion for said subject in a monitored lead and selected frequency band range;

calculating corresponding representative parameter(s) and corresponding ratio(s) involving representative parameters from resulting composite data sets calculated in steps b. and d., in said selected frequency band ranges for monitored (ECG) system lead(s), for respectively, said normal subject population and said subject;

f. comparing specific subject and corresponding specific normal subject population representative parameter(s), and combining results thereof with the results of comparing specific ration(s) of subject to corresponding specific ratio(s) of normal subject population representative parameters, to arrive at a "score", the magnitude of which "score" results from difference(s) in magnitude(s) between corresponding subject and normal subject population representative parameter(s) and difference(s) between magnitude(s) of corresponding ratio(s) of normal subject population, and ratio(s) of subject representative parameters, which "score" magnitude increases when difference(s) in magnitude(s) between corresponding subject and normal subject population representative parameter(s) increase and difference(s) in magnitude(s) between ratio(s) of corresponding normal subject population, and ratio(s) of subject representative parameters increase, the magnitude of which "score" provides an indication of the cardiac status of said subject, with a "score" near zero being indicative of a subject properly categorized as a cardiac normal in that magnitude(s) of subject representative parameter(s) are generally more closely matched to the magnitude(s) of corresponding normal subject population representative parameter(s) and magnitude(s) of ratio(s) of subject representative parameters are generally more closely matched to the magnitude(s) of corresponding ratio(s) of normal subject population representative parameters, and with a progressively higher "score" being indicative of a subject progressively more properly categorized as a cardiac abnormal in that magnitude(s) of subject representative parameter(s) are generally progressively less closely matched to the magnitude(s) of corresponding normal subject population representative parameter(s) and magnitude(s),of ratio(s) of subject representative parameter(s) are generally progressively less closely matched to the magnitude(s) of ratio(s) of corresponding normal subject population representative parameters.

20. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 19, which further comprises performance of the step of applying a confidence level acceptance test to results of comparing subject, to corresponding normal subject population representative parameter(s), and the results of comparing ratios of subject representative parameters to corresponding ratios of normal subject population representative parameters, prior to combining results thereof to arrive at a "score", said confidence level test comprising:

a. the step of determining mean and standard deviation acceptance parameters for specific normal subject population representative parameter(s) and specific ratio(s) of normal subject population representative parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said population of normal subjects was calculated;

b. the step of determining an acceptance parameter for each corresponding specific subject representative parameter and each corresponding specific ratio of subject representative parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said subject was calculated; and

c. the step of accepting the results of comparing a specific subject representative parameter to a corresponding specific normal subject population representative parameter in arriving at said "score", only if the acceptance parameter for said specific subject representative parameter is set off by at least one associated normal subject population acceptance standard deviation from the acceptance mean of the corresponding specific normal subject population representative parameter; and

accepting the results of comparing a specific ratio of subject representative parameters to a corresponding specific ratio of representative parameters for said normal subject population, in arriving at said "score", only if the acceptance parameter of said specific ratio of said subject representative parameters is set off by at least one associated normal subject population acceptance standard deviation from the acceptance mean of said corresponding specific ratio of normal subject population representative parameters.

21. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 19, which further comprises performance of the steps of:

a. providing at least one coordinate system selected from the group consisting of magnitude vs. time, and magnitude vs. frequency;

b. for an (ECG) cycle portion, performing calculations necessary to plot and display and plotting and displaying normal subject population and subject (ECG) data for at least one frequency band range, as a function of at least one parameter selected from the group consisting of time and frequency, to respectively provide as desired, visually interpretable plots of (ECG) magnitude and power spectral density data, observation of which provides an indication of the cardiac status of said subject; and

c. observing and interpreting displayed plot(s).

22. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 19, in which the step of comparing corresponding subject, to normal subject population, representative parameter(s) and ratio(s) thereof, and combining the results thereof to arrive at a "score", which "score" provides an indication of the presence or absence of cardiac abnormality in said subject, includes performance of the step of selecting representative parameter(s) and ratio(s) thereof formed between representative parameters from the group consisting of root-mean-square mean and root-mean-square standard deviation.

23. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom, said method comprising, in a functional sequence, performance of the steps of:

a. obtaining (ECG) data from (ECG) cycle(s) at each lead of a three lead Frank X-Y-Z (ECG) system, from each of a multiplicity of subjects who have been documented as normal subjects, in that they do not show risk factors for, or demonstrate detectable cardiac abnormality;

b. selecting the QRS portion of said obtained (ECG) cycle(s) obtained from each Frank X-Y-Z (ECG) system lead and calculating an average selected QRS cycle portion data set for each monitored Frank (X-Y-Z) (ECG) system lead, by, for each Frank (X-Y-Z) (ECG) system lead, a procedure comprising combining corresponding QRS cycle portion data points for said selected QRS cycle portion for (ECG) cycle(s) obtained from each of a number of members of said multiplicity of members of a population of subjects who have been documented as normal subjects, and selecting a plurality of frequency bands and applying filtering techniques, to provide a plurality of data sets for each Frank X-Y-Z (ECG) system lead, each said data set being a composite QRS data set for said population of normal subjects, for a Frank (X-Y-Z) (ECG) system lead, in a selected frequency band range;

c. obtaining (ECG) data from (ECG), cycle(s) from each Frank X-Y-Z (ECG) system lead for a subject;

d. selecting the QRS complex of said obtained (ECG) cycle(s) obtained at each Frank X-Y-Z (ECG) system lead, said (ECG) QRS cycle portion being the same as that selected in step b. for said normal subject population, and calculating an average selected QRS cycle portion data set for each monitored Frank (X-Y-Z) (ECG) system lead, by, for each Frank (X-Y-Z) (ECG) system lead, a procedure comprising combining corresponding QRS cycle portion data points for said selected QRS cycle portion for subject (ECG) cycle(s), and selecting a plurality of frequency bands, said frequency bands being the same as those selected in step b. for said normal subject population and applying filtering techniques which are the same as those applied in step b. for said normal subject population, to provide a plurality of data sets for each Frank X-Y-Z (ECG) system lead, each said data set being a composite QRS data set for said subject, for a Frank (X-Y-Z) (ECG) system lead, in a selected frequency band range;

e. calculating corresponding root-mean-square mean and root-mean-square standard deviation parameter(s) as well as corresponding ratio(s) involving root-mean-square and root-mean-square standard deviation parameters from resulting composite QRS data sets calculated in steps b. and d., in each selected frequency band range for each Frank X-Y-Z (ECG) system lead, for, respectively, said normal subject population and subject;

f. comparing specific subject and corresponding specific normal subject population root-mean-square parameter(s), and combining results thereof with the results of comparing specific ratio(s) of subject to corresponding specific ratio(s) of normal subject population root-mean-square parameters, to arrive at a "score", the magnitude of which "score" results from difference(s) in magnitude(s) between corresponding subject and normal subject population root-mean-square parameter(s) and difference(s) between magnitude(s) of corresponding ratio(s) of normal subject population, and ratio(s) of subject root-mean-square parameters, which "score" magnitude increases when difference(s) in magnitude(s) between corresponding subject and normal subject population root-mean-square parameter(s) increase and difference(s) in magnitude(s) between ratio(s) of corresponding normal subject population, and ratio(s) of subject root-mean-square parameters increase, the magnitude of which "score" provides an indication of the cardiac status of said subject, with a "score" near zero being indicative of a subject properly categorized as a cardiac normal in that magnitude(s) of subject root-mean-square parameter(s) are generally more closely matched to the magnitude(s) of corresponding normal subject population root-mean-square parameter(s) and magnitude(s) of ratio(s) of subject root-mean-square parameters are generally more closely matched to the magnitude(s) of corresponding ratio(s) of normal subject population root-mean-square parameters, and with a progressively higher "score" being indicative of a subject progressively more properly categorized as a cardiac abnormal in that magnitude(s) of subject root-mean-square parameter(s) are generally progressively less closely matched to the magnitude(s) of corresponding normal subject population root-mean-square parameter(s) and magnitude(s) of ratio(s) of subject root-mean-square parameter(s) are generally progressively less closely matched to the magnitude(s) of ratio(s) of corresponding normal subject population root-mean-square parameters.

24. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 23, which further comprises performance of the step of applying a confidence level acceptance test to results of comparing corresponding specific normal subject population to specific subject root-mean-square parameters, and corresponding specific ratios of said root-mean-square parameters of subject, to specific ratios of normal subject population, root-mean-square parameters prior to combining results thereof to arrive at a "score", said confidence level test comprising:

a. the step of determining mean and standard deviation acceptance parameters for specific normal subject population root-mean-square parameter(s) and specific ratio(s) of normal subject population root-mean-square parameter(s) based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said population of normal subjects was calculated;

b. the step of determining an acceptance parameter for each specific corresponding subject root-mean-square parameter and each corresponding specific ratio of subject root-mean-square parameters based upon the (ECG) data from which said composite data set of said selected (ECG) cycle portion for said subject was calculated; and

c. the step of accepting the results of comparing a specific subject root-mean-square parameter to a corresponding specific normal subject population root-mean-square parameter in arriving at said "score", only if the acceptance parameter for said specific subject root-mean-square parameter is set off by at least one associated normal subject population acceptance standard deviation from the acceptance mean of the corresponding specific normal subject population root-mean-square parameter; and

accepting the results of comparing a specific ratio of subject root-mean-square parameters to a corresponding specific ratio of root-mean-square parameters for said normal subject population, in arriving at said "score", only if the acceptance parameter of said specific ratio of said subject root-mean-square parameters is set off by at least one associated normal population acceptance standard deviation from the acceptance mean of said corresponding specific ratio of normal subject population root-mean-square parameters.

25. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 24, in which the step applying a confidence level test for accepting differences between corresponding normal subject population to subject root-mean-square parameters, and corresponding ratios of said root-mean-square parameters, for each Frank X-Y-Z (ECG) system lead and using said accepted differences to arrive at a "score", includes performing the step of determining if an acceptance parameter of the subject falls outside a region of distribution of corresponding normal subject population data, centered around an acceptance mean for said corresponding normal subject population, which region of distribution of normal subject population data includes ninety-five (95%) percent of said corresponding normal subject population distribution data.

26. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 23, which includes in performance of the step of applying filtering techniques in steps b. and d. thereof, the specific formation of fifteen (15) data sets for each of the normal subject population and the subject, said data sets being five (5) per each Frank X-Y-Z (ECG) system lead, said five (5) data sets per each Frank X-Y-Z (ECG) system lead covering:

a. all frequencies present;

b. the frequency range of zero (0) to ten (10) Hertz;

c. the frequency range of ten (10) to sixty (60) Hertz;

d. the frequency range of sixty (60) to one-hundred-fifty (150) Hertz; and

e. the frequency range of one-hundred-fifty (150) to two-hundred-fifty (250) Hertz.

27. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 23, which further comprises performance of the steps of:

a. providing at least one coordinate system selected from the group consisting of magnitude vs. time, and magnitude vs. frequency;

b. for an (ECG) cycle portion, performing calculations necessary to plot and display and plotting and displaying normal subject population and subject (ECG) data for at least one frequency band range, as a function of at least one parameter selected from the group consisting of time and frequency, to respectively provide as desired, visually interpretable plots of (ECG) magnitude and power spectral density data, observation of which provides an indication of the cardiac status of said subject; and

c. observing and interpreting displayed plot(s).

28. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 23, in which corresponding ratios of said root-mean-square parameters are compared, said method including performance of the steps of:

a. selecting said ratios to be calculated as, for each (ECG) lead and frequency band range utilized, a root-mean-square mean for said frequency band range divided by a sum of root-mean-square means of all frequency band ranges present;

said ratio for a normal subject population being subtracted from a corresponding ratio for said subject, each said subtracted difference being divided by a root-mean-square standard deviation for said normal subject population in a corresponding frequency band range; and

b. performing the calculations described in step a.

29. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom as in claim 23, in which corresponding ratios of said root-mean-square parameters are compared, includes performance of the steps of:

a. selecting said ratios to be calculated as, for each (ECG) lead and frequency band range utilized, a root-mean-square mean for one (ECG) lead divided by a root-mean-square mean for another (ECG) lead;

said ratio for a normal subject population being subtracted from a corresponding ratio for said subject, each said subtracted difference being divided by a root-mean-square standard deviation for said normal subject population ratio in a corresponding frequency band range; and

b. performing the calculations described in step a.

30. A noninvasive method of investigating cardiac status of a subject and enabling classification of a subject into normal and abnormal cardiac categories utilizing electrocardiography (ECG) data obtained therefrom, said method comprising, in a functional sequence, performance of the steps of:

a. obtaining data from (ECG) cycle(s) from each of a multiplicity of members of a population of subjects who have been documented as normal subjects, in that they do not show risk factors for, or demonstrate detectable cardiac abnormality, by monitoring at least one lead(s) of an (ECG) system;

b. selecting some (ECG) cycle portion and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s), by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for (ECG) cycle(s) obtained from each of a number of said multiplicity of members of a population of subjects who have been documented as normal subjects, and selecting a plurality of frequency bands and applying filtering techniques, to provide a plurality of data sets for said at least one (ECG) system lead(s) monitored, each said data set being a composite data set of said selected (ECG) cycle portion for said population of normal subjects in a monitored lead and selected frequency band range;

c. obtaining data from (ECG) cycle(s) from a subject, by monitoring at least one lead(s) of an (ECG) system, said (ECG) system lead(s) monitored being the same as the monitored (ECG) system lead(s) utilized in step a. to obtain data utilized in step b.;

d. selecting some (ECG) cycle portion, said (ECG) cycle portion being the same as that selected in step b. for said normal subject population, and calculating an average selected (ECG) cycle portion data set for at least one monitored (ECG) system lead(s), by, for a monitored (ECG) system lead, a procedure comprising combining corresponding (ECG) cycle portion data points for said selected (ECG) cycle portion for subject (ECG) cycle(s), and selecting a plurality of frequency bands, said selected frequency bands being the same as those selected in step b. for said normal subject population, and applying filtering techniques which are the same as those applied in step b. for said normal subject population, to provide a purality of data sets for said at least one monitored (ECG) system lead(s), each said data set being a composite data set of said selected (ECG) cycle portion for said subject in a monitored lead and selected frequency band range;

e. performing at least one of the following steps f. and g.;

f. calculating mean and standard deviation representative parameters from at least one resulting composite data set calculated in step b., said mean and standard deviation parameters being from a selected frequency band range for a monitored (ECG) system lead, and providing a coordinate system consisting of magnitude vs. time on ordinate and abscissa respectively and plotting and displaying on said coordinate system loci consisting of;

31. normal subject population standard deviation bounds located above and below said normal subject population mean, anda corresponding subject data set,

then observing differences between normal subject population and subject data plots, with a subject data set falling within the normal subject standard deviation bounds being indicative of a subject properly classified as a cardiac normal, and with a subject data set falling progressively further outside said normal subject standard deviation bounds being indicative of a subject progressively more properly classified as a cardiac abnormal;

g. calculating power spectral density data for at least one resulting composite data set calculated in step b. and for a corresponding resulting composite data set calculated in step d. for a selected frequency band range for a monitored (ECG) system lead, and providing a coordinate system consisting of magnitude vs. frequency on ordinate and abscissa respectively and plotting and displaying on said coordinate system power spectral density data loci, then observing differences between normal subject population and subject data loci, with closely matched corresponding subject and normal subject population data set power spectral density loci being indicative of a subject properly classified as a cardiac normal and with progressively more mismatched subject and normal subject population data set power spectral density loci being indicative of a subject progressively more properly classified as a cardiac abnormal.