An Electrocardiogram Classification for Irregular Heart Beats with Artificial Neural Network

A classification of arrhythmia is first to detect the heart beats and classify its their types. However, the missing heart beats and mistaken heart beats must be existed when heart beats are detected. If these false heart beats were mixed in the normal sinus rhythm (NSR) beats and the irregular sinus rhythm (ISR) beats, how to classify these false heart beats is a challenge. In this study, we propose an automatic configuration to consider the problem of false heat beat. It integrating digital signal processing and artificial intelligence could detect the heart beats and recognize these heart beats as belonging to the NSR, ISR, or false heart beat. The results show that the accuracy of false heart beats is 96.8%.