a method of analyzing experimentally derived electrocardiograph 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 , 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 , , values for a composite ecg waveform present in a compiled data bank derived from 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 .