Non-stationary analysis of electrocardiograms (ECGs) using Wigner-Ville distribution is presented. Analysis was performed on subjects with acute myocardial infarction who had undergone thrombolysis, in Holter recordings of lead V1. The distinction between successfully and non-successfully thrombolysed patients was evaluated, based on time-frequency features of the Wigner-Ville transformed ECGs at the sixth hour after lysis. Characteristic parameters were extracted from time-frequency areas, and linear discriminant analysis was performed on these parameters, leading to a prediction index to distinguish the two classes. Thirteen features were found statistically significant by t-test and were used for the classification with linear modelling. Out of these features, four corresponded to frequencies lower than 25 Hz and higher than 50 Hz for, roughly, the QRS complex, five features corresponded to all the frequency bands of, roughly, the ST area, and the last four features corresponded to the T-wave. The feature-vector used in linear modelling was iteratively generated, and the iterative prediction found all 18 features significant. The iterative method resulted in better classification than that of the standard statistical procedure (3.8% error against 18.1% with the classic method). The evolution of the prediction index with time for the first 12 h was different for the successfully and non-successfully thrombolysed groups. Specifically, in the successful thrombolysis group, oscillations and variation with time were more obvious, indicating a possible difference in the dynamics of the cardiac system.