India
Research Article
Classification of Arrhythmia using Wavelet Transform and Neural Network Model
Author(s): Siva A, Hari Sundar M, Siddharth S, Nithin M and Rajesh CBSiva A, Hari Sundar M, Siddharth S, Nithin M and Rajesh CB
Cardiovascular diseases are a major cause of death. Change in normal human heart beat may result in different types of cardiac arrhythmias. An Irreversible damage to the heart is possible. In this paper a method is proposed to classify different arrhythmias and normal sinus rhythm, through a combination of wavelet Transform and Artificial Neural Networks (ANN) accurately and efficiently. Adaptive filtering using Recursive Least squares (RLS) adaptive algorithm is utilized to nullify AC and DC noises from the sample ECG signal set. ECG data’s are collected from MITBIH database. As ECG signal is a non- stationary signal wavelet transform is used to decompose the signal at various resolutions. This allows accurate detection and extraction of features. In our approach, discrete wavelet transforms (DWT) coefficients set is obtained from wavelet decomposition which would contain the m.. Read More»
DOI:
10.4172/2155-9538.1000244
Journal of Bioengineering & Biomedical Science received 307 citations as per Google Scholar report