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 accurate catagorization of subjects into various abnormal and normal classifications is disclosed. The presently preferred embodiment applies an algorithm which compares representative parameter, (eg. root-mean-square (RMS) mean), values derived from analysis of a selected portion of a single cycle of an ECG PQRST waveform obtained from investigation of a subject, to similarly derived representative parameter, (eg. RMS mean and RMS standard deviation), values for a composite ECG waveform present in a compiled data bank derived from (ECG) investigation of numerous subjects who were documented as normals, typically 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 method is directly adapted to tracking subject cardiac status change by substituting a baseline subject data set for the normal population data set.normal population data set.