Abstract: This research paper describes a novel method in which analysis of the ElectroCardioGraphy (ECG) signals is done using the hybrid classifier. As it is an already known fact that ECG signals are used by doctors to diagnose the heart activity of the subject and on the basis of knowledge about its peaks, treatment of the disease is done. Hence, the purpose of this research work is to identify the Normal, Apnea, Ischemia and Tachycardia signals using the method of Principal Component Analysis (PCA) and Neuro-Fuzzy classifier. PCA algorithm is used to extract the relevant information from the ECG input dataset which are their P-QRS-T parameters values. Then the extracted features data is analyzed and classified using the hybrid of Artificial Neural Networks (ANN) and Fuzzy Logic classifiers i.e. Neuro-Fuzzy classifier. Then these classification results are compared and observed a good accuracy of around 96% in the classification.
Keywords: ANN, ECG, Fuzzy, Neuro-Fuzzy, PCA.