{"title":"ECG Analysis using Nature Inspired Algorithm","authors":"A.Sankara Subramanian, G.Gurusamy, G.Selvakumar, P.Gnanasekar, A.Nagappan","volume":60,"journal":"International Journal of Biomedical and Biological Engineering","pagesStart":647,"pagesEnd":652,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/15617","abstract":"This paper presents an algorithm based on the\nwavelet decomposition, for feature extraction from the ECG signal\nand recognition of three types of Ventricular Arrhythmias using\nneural networks. A set of Discrete Wavelet Transform (DWT)\ncoefficients, which contain the maximum information about the\narrhythmias, is selected from the wavelet decomposition. After that a\nnovel clustering algorithm based on nature inspired algorithm (Ant\nColony Optimization) is developed for classifying arrhythmia types.\nThe algorithm is applied on the ECG registrations from the MIT-BIH\narrhythmia and malignant ventricular arrhythmia databases. We\napplied Daubechies 4 wavelet in our algorithm. The wavelet\ndecomposition enabled us to perform the task efficiently and\nproduced reliable results.","references":"[1] Anant K., F. Dowla and G.Rodrigue, \"Vector quantization of ECG\nwavelet coefficients\", IEEE Signal Processing Letters, Vol. 2, No. 7,\nJuly, 1995.\n[2] M.Vetterli, \"Wavelets and filter banks: theory and design\", IEEE\nTransactions on Signal Processing, Sep, 1992, pp 2207 - 2232.\n[3] R.M.Rao, A.S.Bopardikar, \"Wavelet transforms: Introduction to theory\nand applications\", Addison Wesley Longman, 1998.\n[4] L.Khadra, A.S.Al-Fahoum, H.Al-Nashash, \"Detection of life threatening\ncardiac arrhythmia using the wavelet transformation\", Med. Biol. Eng.\nComput., Vol. 35, 1997, pp. 626-632.\n[5] Addison P.S., Watson J.N., Clegg G.R., Holzer M., Sterz F. and\nRobertson C.E., \u00d4\u00c7\u00ffEvaluating arrhythmias in ECG signals using wavelet\ntransforms-, IEEE Engineering in Medicine and Biology Magazine, Vol.\n19, pp. 104-109, 2000.\n[6] Dinh H.A.N., Kumar D.K., Pah N.D. and Burton P., \u00d4\u00c7\u00ffWavelets for QRS\ndetection-, Proceedings of the 23rd Annual Conference, IEEE EMS,\nIstanbul, Turkey, pp. 35-38, 2001.\n[7] Kadambe S., Murray R. and Boudreaux-Bartels G.F., \u00d4\u00c7\u00ffWavelet\ntransform based QRS complex detector-, IEEE Transaction on\nBiomedical Engineering, Vol. 46, No. 7, pp. 838-848, 1999.\n[8] Romero I., Serrano L. and Ayesta, \u00d4\u00c7\u00ffECG frequency domain features\nextraction: A new characteristic for arrhythmias classification-,\nConference of the IEEE Engineering in Medicine and Biology Society,\n2001.\n[9] Szilagyi S.M. and Szilagyi L., \u00d4\u00c7\u00ffWavelet Transform and Neural Network\nbased Adaptive Filtering for QRS Detection-, Proceedings of World\nCongress on Medical Physics and Biomedical Engineering, Chicago,\nUSA, 2000.\n[10] Rumelhart D.E., Hinton G.E. and Williams R.J., \"Learning\nrepresentations by back-propagation errors\", Nature, 1986.\n[11] V.X.Afonso, W.J.Tompkins, \"Detecting ventricular fibrillation\", IEEE\nEng. Boil., March\/April, 1995, pp. 152-159.\n[12] Selvakumar G., Bhoopathy Bagan K. and Chidhambara Rajan B.,\n\u00d4\u00c7\u00ffWavelet Decomposition for Detection and Classification of Critical\nECG Arrhythmias-, Proc. of the 8th WSEAS Int. Conf. on Mathematics\nAnd Computers in Biology and Chemistry, Vancouver, Canada, June 19-\n21, 2007.\n[13] A.S. Al-Fahoum, I.Howitt, \"Combined wavelet transformation and\nradial basis neural networks for classifying life threatening cardiac\narrhythmias\", Med. Biol. Eng. Comput., Vol. 37, 1999, pp. 566 - 573.\n[14] MIT-BIH (http:\/\/www.physionet.org)\n[15] Dorigo M., Caro GD, Gambardella L.M. Ant algorithms for discrete\noptimization. Artiff Life 1999;5, pp 137-142\n[16] Dorigo M, Maniezzo and Colomi A. \" Ant system: optimization by a\nclolony of cooperating agents\", IEEE Trans. Systems, Man and\nCybernetics- part B, Vol 26, pp 29-41 Feb 1996\n[17] Tsai C-F, Tsai C-W, Wu H-C Yang T . A novel data clustering approach\nfor data mining in large databases, Journal of System and Software, 2004\n73:133-45","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 60, 2011"}