A Review of ECG Peaks Detection and Classification

Abstract

This paper describes several methods used in identifying peaks of Electrocardiogram (ECG) signals. Precise recognition of ECG peaks will provide useful information for doctors to diagnose any heart disorder or abnormalities as well as for cardiac arrhythmias classification. Generally, several methods have been applied in detecting real ECG peaks. These include template matching, wavelet transform, fuzzy logic and neural network. A review based on technical works, experimental testing and investigation from experts, researchers and professionals have been carried out to analyze the techniques in terms of accuracy and suitability for ECG analysis. In addition, this paper summarizes details of technical works done by others based on their respective methods. As a result, neural network is proposed for future ECG implementation systems due to its unique characteristics even though some limitations of the network might also be inherent.