Ventricular Arrhythmia Detection Techniques for ECG Signal: A Survey Approach

Forfattere

  • Taru Aggarwal Dept. of Electrical, Electronics and Communication, ITM University, Gurgaon, India
  • Sharda Vashisth Dept. of Electrical, Electronics and Communication, ITM University, Gurgaon, India

Nøgleord:

Arrhythmia, Electro Cardio Graph (ECG), Fibrillation, Ventricular Tachycardia (VT), Ventricular Flutter (VF)

Resumé

Electrocardiogram (ECG) represents the electrical activity of the heart and is used to measure the rate and regularity of heartbeats. In this paper we propose a method for an Independent Component Analysis (ICA) based detection and classification of the ventricular arrhythmia. The malignant ventricular arrhythmia database from www.physionet.org/physiobank/database/vfdb has been utilized for evaluating the algorithm over MATLAB interface. This scheme assimilates ICA and probabilistic neural network for classifying critical arrhythmia like Ventricular Fibrillation, Ventricular Flutter and V-Tachycardia into VF rhythms and decomposes ECG signals that are statistically mutual independent into basis vectors that serve as ICA components and when projected with RR interval constitutes the feature vector. The independent components (ICs) are arranged strategically for their selection. Probabilistic neural network will be used as a classifier to evaluate the proposed method. The selected features are used to train the classiï¬er to recognize different ventricular arrhythmias.  Keywords: Arrhythmia, electro cardio graph (ECG), fibrillation, ventricular tachycardia (VT), ventricular flutter (VF)Cite this Article Taru Aggarwal, Sharda Vashisth. Ventricular Arrhythmia Detection Techniques for ECG Signal: A Survey Approach. Research and Reviews: Journal of Neuroscience (RRJoNS). 2015; 5(1): 25–30p.

Downloads

Publiceret

2015-04-29

Nummer

Årg. 5 Nr. 1 (2015)

Sektion

Review Articles

Licens

Declaration and Copyright Transfer Form

(to be completed by authors)

I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.

·         I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.

·         I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).

·         I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.

·          I/We also agree to the authorship of the article in the following order:

Author’s name                                    

 

1. ________________

2. ________________

3. ________________

_______________

We  Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal.