Wireless Identification and Classification of Arrhythmias on Portable ECG Using ANN Method

Abstract

Heart disease, especially Arrhythmia cannot be seen directly because there are no symptoms, and can only be known by carrying out an examination by a medical expert or using an electrocardiograph (ECG). Most current ECG devices cannot perform classification directly. For this purpose, a classification system that has high accuracy is needed so that the results of the analysis can be credible. The Artificial Neural Network method is one of the methods offered because it is suitable for dealing with complex classification problems. In this study, a classification model will be created based on heart wave parameters for Arrhythmia detection. The results of the classification model made have an accuracy of 94.12%. The developed model can help the process of classifying heart disease which is difficult to diagnose.