Real Time ECG Feature Extraction and Arrhythmia Detection on a Mobile Platform

Abstract

means abnormal rate of heart contraction which is dangerous as it may also cause death. The work proposed in this paper mainly deals with the development of an efficient arrhythmia detection algorithm using ECG signal so that detection of arrhythmia at initial stages is possible using a smart-phone which is readily available anywhere which makes complete system mobile. Subjects for experiments included normal patients, patients with Bradycardia, Tachycardia, atrial premature contraction (APC), patients with ventricular premature contraction (PVC) and patients with Sleep Apnea. Pan-Tompkins algorithm was used to find the locations of QRS complexes and R Peaks. The algorithm to detect different arrhythmia is based on position of P wave, QRS complex, R Peak and T wave and on interval between these waves on android smart-phone. The algorithm was tested using MIT-BIH arrhythmia database. Results revealed that the system is accurate and efficient to classify arrhythmias as high overall performance (97.3%) for the classification of the different categories of arrhythmic beats was achieved. The proposed arrhythmia detection algorithm may therefore be helpful to the clinical diagnosis.