@article{(Open Science Index):https://publications.waset.org/pdf/15617,
	  title     = {ECG Analysis using Nature Inspired Algorithm},
	  author    = {A.Sankara Subramanian and  G.Gurusamy and  G.Selvakumar and  P.Gnanasekar and  A.Nagappan},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Biomedical and Biological Engineering},
	  volume    = {5},
	  number    = {12},
	  year      = {2011},
	  pages     = {647 - 651},
	  ee        = {https://publications.waset.org/pdf/15617},
	  url   	= {https://publications.waset.org/vol/60},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 60, 2011},