In recording an electrocardiogram (ECG), an interchange of electrodes may easily go unnoticed. Automatic detection would be desirable, but current algorithms, when dealing with more than left arm-right arm reversal, have moderate sensitivity. We propose a novel approach that uses the redundancy of information in the standard 12-lead ECG. We assume that each of the 8 independent electrocardiographic leads can be reconstructed from the 7 others in reasonable approximation. The correlation between any electrocardiographic lead and its reconstruction should be higher if the electrodes are correctly placed than when some interchange were present. The difference in correlation should have discriminative power. This was verified on a set of 3,305 ECGs for 14 common electrode interchange errors. The material was split in a learning and test set, and general reconstruction coefficients were computed from the learning set. For each interchange, electrode-error ECGs were derived by rearranging leads of the unaltered ECGs. Correlations between the actual leads and their reconstructions were computed for all ECGs. From the differences in lead correlation, decision rules were derived for each kind of interchange. All 14 rules had specificities of ≥99.5% in the test set. Sensitivities were ≥93% for 11 rules, and left arm-left leg electrode reversal scored low.