An automated system for ST segment and arrhythmia analysis in exercise radionuclide ventriculography.

Abstract

A computer-based system for interpretation of the electrocardiogram (ECG) in the diagnosis of arrhythmia and ST segment abnormality in an exercise system is presented. The system was designed for inclusion in a gamma camera so that ECG diagnosis could be combined with the diagnostic capability of radionuclide ventriculography. Digitized data are analyzed in a beat-by-beat mode and a contextual diagnosis of underlying rhythm is provided. Each beat is assigned a beat code based on a combination of waveform analysis and RR interval measurement. The waveform analysis employs a new correlation coefficient formula which corrects for baseline wander. Selective signal averaging, in which only normal beats are included, is done for an improved signal-to-noise ratio prior to ST segment analysis. Template generation, R wave detection, QRS window size, baseline correction, and continuous updating of heart rate have all been automated. ST level and slope measurements are computed on signal-averaged data. Arrhythmia analysis of 13 passages of abnormal rhythm by computer was found to be correct in 98.4 percent of all beats. 25 passages of exercise data, 1-5 min in length, were evaluated by the cardiologist and found to be in agreement in 95.8 percent in measurements of ST level and 91.7 percent in measurements of ST slope.