R-Peaks Detection Method for Classifying Arrhythmia Disorder

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.