R-Peaks Detection Method for Classifying Arrhythmia Disorder

Anggit Ferdita Nugraha (Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta)
Brahmantya Aji Pramudita (Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta)
Noor Akhmad Setiawan (Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta)
Hanung Adi Nugroho (Department of Electrical Engineering and Information Technology, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta)

Journal of the Medical Sciences (Berkala Ilmu Kedokteran)
Vol 49, No 4 (2017)

Electrocardiography (ECG) is a non-invasive technique that is used to diagnose heartabnormalities. ECG records all heart activities and represent them using bio electricsignals. 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 diseaseas deadly as coronary heart disease and heart failure. Arrhythmia described using thedifference between the R-peaks based on QRS complex. Therefore, R-peaks detection willbe an important factor that can be used to classify arrhythmia disease. One of the widelyused methods to detect R-peaks is Pan-Tompkins method. Pan-Tompkins method used athreshold value approach to get all location of R-peaks point from the ECG signals. Thisstudy proposed a development based on Pan-Tompkins method by change the thresholdvalue using normalize technique and moving windows approach to get all location ofR-peaks point from the ECG signals. This study uses MIT-BIH arrhythmia dataset. Thismethod can show the R-peaks detection with 99.83% sensitivity and 0.40% total errorrate detection. Hence, this method has potential to be used for classifying arrhythmiadisorder based on the R-peaks point.