Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/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 Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering},  volume    = {5},
  number    = {12},
  year      = {2011},
  pages     = {647 - 651},
  ee        = {http://waset.org/publications/15617},
  url       = {http://waset.org/Publications?p=60},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 60, 2011},
}