Classification and Processing of MIT-BIH Arrhythmia-Based on BP Algorithm

Abstract

ECG recognition is of great significance to the diagnosis of heart diseases. Based on the data of the MIT-BIH Arrhythmia Database, a more accurate ECG signal map was extracted using wavelet transform, a BP neural network was constructed for pattern recognition, and five types of arrhythmia-sinus arrhythmia, premature beats, Yibo, sinoatrial block, and atrial block. And compared with the BP network using SVM and K nearest neighbor algorithm, it is found that the BP network performs better.