Engglis

Abstract

Electrocardiography (ECG) is a non-invasive technique that is used to diagnose heart abnormalities. ECG records all heart activities and represent them using bio electric signals. Arrhythmia is one of the cardiac disorder that can be detected using ECG. Arrhythmia need to be detected early because of an early symptom of heart disease as deadly as coronary heart disease and heart failure. Arrhythmia described using the difference between the R-peaks based on QRS complex. Therefore, R-peaks detection will be an important factor that can be used to classify arrhythmia disease. One of the widely used methods to detect R-peaks is Pan-Tompkins method. Pan-Tompkins method used a threshold value approach to get all location of R-peaks point from the ECG signals. This study proposed a development based on Pan-Tompkins method by change the threshold value using normalize technique and moving windows approach to get all location of R-peaks point from the ECG signals. This study uses MIT-BIH arrhythmia dataset. This method can show the R-peaks detection with 99.83% sensitivity and 0.40% total error rate detection. Hence, this method has potential to be used for classifying arrhythmia disorder based on the R-peaks point.