Three approaches for detecting abnormalities in body surface potential maps recorded from patients with myocardial infarction were evaluated. The maps are generated from 26 simultaneously recorded unipolar electrocardiograms. All three approaches detect the deviations in certain parameters from control values determined from 50 normal subjects. The first approach emphasizes qualitative deviations in the trajectories of the surface potential map extrema during QRS and correctly classified all but one infarct in a test group comprising 30 normals and 30 cases of myocardial infarction. The second approach classifies a test subject as abnormal if any one of his 26 lead waveforms deviates appreciably at any instant during QRS from the mean waveform for the particular lead plus or minus two standard deviations, these being determined from the control group. This method, while correctly identifying all infarcts, resulted in a large number of false positives, misclassifying 22 of 30 normals. A final method was to obtain an instant by instant plot of the correlation coefficient between the mean surface potential map during QRS for the 50 normals and that of the subject being tested. Test cases were classified as abnormal if any correlation coefficient value fell below an envelope determined from the correlation coefficient plots obtained by correlating the maps of all 50 normals with their own mean. Twenty-nine normals and 26 infarcts were correctly classified. On the basis of these results, the first approach is superior to the other two for detecting surface potential map abnormalities in patients with myocardial infarction.