A noninvasive method for identifying coronary disfunction utilizing electrocardiography derived data

摘要

A method of analyzing experimentally derived electrocardiograph (ECG) data, and system for practicing said method, which allow tracking of subject cardiac status change and which allow 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 representative parameter, (eg. 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 representative parameter, (eg. 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 time domain and power spectral density plots enhance the method. In addition, comparison of the calculated "Score" to subject cardiac ejection fraction provides indication of risk for sudden death as does the presence of "rhomboids" following a QRS complex in frequency domain plots. The present invention is directly adapted to tracking subject cardiac status change by substituting a baseline subject data set for the normal population data set.