Principal Component Analysis Method for Detection and Classification of ECG Beat

Abstract

This study proposes a simple and effective method, termed Principal Component Analysis (PCA) method, to analyze ECG signals for effectively determining the heartbeat case. This method is easily performed and does not require complex mathematic computations. The average time required for processing a 30-minute long of ECG data is less than 1 minute, and the required maximum memory is only about 10 MB. The ECG records available in the MIT-BIH arrhythmia database are utilized to illustrate the effectiveness of the proposed method. The experiment results show the total classification accuracy was approximately 90.85%.