Open Science Research Excellence
%0 Journal Article
%A A.Sankara Subramanian and  G.Gurusamy and  G.Selvakumar and  P.Gnanasekar and  A.Nagappan
%D 2011 
%J  International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 60, 2011
%T ECG Analysis using Nature Inspired Algorithm
%U http://waset.org/publications/15617
%V 60
%X This paper presents an algorithm based on the
wavelet decomposition, for feature extraction from the ECG signal
and recognition of three types of Ventricular Arrhythmias using
neural networks. A set of Discrete Wavelet Transform (DWT)
coefficients, which contain the maximum information about the
arrhythmias, is selected from the wavelet decomposition. After that a
novel clustering algorithm based on nature inspired algorithm (Ant
Colony Optimization) is developed for classifying arrhythmia types.
The algorithm is applied on the ECG registrations from the MIT-BIH
arrhythmia and malignant ventricular arrhythmia databases. We
applied Daubechies 4 wavelet in our algorithm. The wavelet
decomposition enabled us to perform the task efficiently and
produced reliable results.
%P 647 - 651