The performance of body surface potential maps and the 12-lead ECG in the detection of old myocardial infarction has been compared in a two-group (54 normals; 52 infarctions) classification procedure (linear discriminant analysis). Three methods for data reduction of body surface maps were compared: 1) time integration, 2) one-step reduction in eigenvectors and 3) two-step reduction in spatial and temporal eigenvectors. Features were taken from the reduction variables by a stepwise selection procedure. From 90% to 93% correct classifications could be obtained using three features from the map data over the initial 30 ms (Q interval) of the QRS wave for all three methods considered. Using the 100 ms (QRS) interval 86% correct classifications were obtained using method 1, and up to 90% and 87% for methods 2 and 3, respectively. In a further analysis the classification based on body surface maps was compared to the one based on the 12-lead ECG. The 12-lead ECG was treated as a restricted set of the body surface mapping leads, so the same methods of data reduction, feature extraction and classification could be applied to both sets of data. Applying method 1 (time integration) 89% correct classifications were obtained using data taken from the 30 ms interval of the 12-lead ECG and a subsequent reduction to three features. When using the 100 ms interval the result was 79% also using three features. The results of method 2 applied to the 12-lead ECG were 89% (30 ms interval, three features) and 78% (100 ms interval, three features).