Clasification of Human Heart Abnormality using Time-frequency and Image Processing Technique

This paper describes heart abnormalities classification procedures utilising features obtained from time-frequency spectogram of ECG heart and image processing technique. Enhanced spatial features of time-frequency spectogram were extracted and fed into a forward chaining expert system and the corresponding abnormalities were identified. A confidence factor is calculated for every classification result indicating the degree of belief that the classification is true. It was observed that the classification methos was able to give 100% correct classification based on features that was extracted from data sets which were included in the knowledge base and data sets which were not included in the knowledge base