An adaptive fuzzy model for ECG interpretation

A new pattern recognition model has been designed for ECG signal classification in general and acute myocardial infarction in specific. This model combines a fuzzy logic inference system with neural network adaptive learning. In this paper, we compare the performance of the proposed system to a neural network only model and a previously designed ECG interpretation program. The initial classification results based on a chest-pain patient database show that the new model has potential for classification accuracy while retaining the knowledge which is particularly useful for clinicians to understand the process of the model.