ECG Signal Fibrillation Classification on Android Platform: A Survey Approach
Kritika Bawa1, Pooja Sabharwal2

1Kritika Bawa, ECE, ITM University,Gurgaon, India.
2Ass. Prof. Pooja Sabharwal,ECE, ITM University, Gurgaon, India.

Manuscript received on May 15, 2014. | Revised Manuscript received on May 18, 2014. | Manuscript published on May 25, 2014. | PP:1-4 | Volume-2 Issue-7, May 2014. | Retrieval Number: G0726052714/2014©BEIESP

Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: Electrocardiography deals with the electrical activity of the heart. The condition of cardiac health is given by ECG and heart rate. Automatic analysis of cardiac diseases is the vast area of research,. In literature there are number of techniques for classification of ECG signal on Android platform. ECG signal is the most commonly used for diagnosing various heart related disease like ventricular fibrillation, artial fibrillation, arrhythmia detection, premature ventricular contraction, Tachycardia, Bradycardia etc,. This paper presents a comparative study of the techniques used in the literature.
Keywords: Ventricular fibrillation, arterial fibrillation, fuzzy, neural networks, ECG