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Classification of ECG Signals using ANN with Resilient Back Propagation Algorithm

by G. Subramanya Nayak, Dayananda Nayak
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 6
Year of Publication: 2012
Authors: G. Subramanya Nayak, Dayananda Nayak
10.5120/8570-2294

G. Subramanya Nayak, Dayananda Nayak . Classification of ECG Signals using ANN with Resilient Back Propagation Algorithm. International Journal of Computer Applications. 54, 6 ( September 2012), 20-23. DOI=10.5120/8570-2294

@article{ 10.5120/8570-2294,
author = { G. Subramanya Nayak, Dayananda Nayak },
title = { Classification of ECG Signals using ANN with Resilient Back Propagation Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 6 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 20-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number6/8570-2294/ },
doi = { 10.5120/8570-2294 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:00.113138+05:30
%A G. Subramanya Nayak
%A Dayananda Nayak
%T Classification of ECG Signals using ANN with Resilient Back Propagation Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 6
%P 20-23
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Electrocardiogram is one important physiological signal, which is used in assessing cardiac health. The extraction of features used for identification of the state of ECG is discussed in this paper. Using MAT LAB programs/tools, different statistical features are extracted from both normal and arrhythmia spectra. These features include arithmetic mean, median, variance, residuals on curve fitting etc. The values of the feature vector reveal information regarding cardiac health state. Then a classical multilayer feed forward neural network with back propagation algorithm is employed to serve as a classifier of the feature vector, giving 100% successful results for the specific data set considered.

References
  1. Jacek M. Zurada , Introduction to Artificial Neural Systems,pp 25–89. Publisher-Pearson Education, 3rd Edition.
  2. B. K. Manjunath,J. Kurien,C. Muralikrishna,Autofluorescence of Oral tissue for optical pathology in Oral malignancy, Journal of Photochemestry and Photobiology B. Biology 73 (2004 ) 49 -58.
  3. George A. Rovithakis and Michail Maniadakis ,Artificial Neural Networks for discriminating Pathologic from Normal Peripheral Vascular Tissue,IEEE transactions on Biomedical Engineering ,vol 48,No 10, october 2001
  4. Sigurdur Sigurdsson et ,al ,Detection of skin cancer by classification of Raman spectra, IEEE transactions on Biomedical Engineering ,2004.
  5. Simon Hykin,Neural Networks-A Comprehensive foundation,section 4. 1to4. 10,page 156-234,Jaico Publishing House,5TH edition.
  6. William Palm J, "Introduction to MATLAB 6 for Engineers".
  7. G. S. Nayak, Sudha Kamath et al. (2006) Principal Component Analysis and Artificial Neural Network Analysis of oral Tissue Fluorescence Spectra: Classification of Normal, Premelignant and Malignant Pathological Condition Biopolymers 82:152-166
  8. G. Subramanya Nayak and Gopallakrishna Prabhu K (2004) Analysis of Electroglottographic Signal for Measurement of Vocal Fold Abduction / Larynx Movement ,using Amplitude Modulation Technique,ECCS-2004 Proc. National Conference on Electronic Circuits and Communication Systems, Patiala, India, 2004, pp 463 – 465.
Index Terms

Computer Science
Information Sciences

Keywords

Electrocardiogram Back propagation algorithm Neural Network

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