Heart beat classification using wavelet feature based on neural network

WSEAS Transactions on Systems

Volumn 10, Issue 1, 2011, Pages 17-26

  Jatmiko, Wisnu ^a   Nulad, W P ^a   Elly, M I ^a,b   Setiawan, I Made Agus ^a,c   Mursanto, P ^a  

^a UNIVERSITY OF INDONESIA   (Indonesia)

^b UNIVERSITAS NEGERI SURABAYA   (Indonesia)

^c UDAYANA UNIVERSITY   (Indonesia)

Author keywords

Arrhythmia; Back propagation; ECG; Electrocardiogram; FLVQ; MIT BIH; Physionet; Wavelet transforms

Indexed keywords

ARRHYTHMIA; ELECTROCARDIOGRAM; FLVQ; MIT-BIH; PHYSIONET;

AUDIO SYSTEMS; BACKPROPAGATION ALGORITHMS; ELECTROCARDIOGRAPHY; ELECTROCHROMIC DEVICES; NEURAL NETWORKS; VECTOR QUANTIZATION;

FEATURE EXTRACTION;

EID: 79958244880     PISSN: 11092777     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (30)

1. C. Nordqvist, "What is arrhythmia? what causes arrhythmia?" http://www.medicalnewstoday.com/articles/888 7.php, May 30th2004. updated September 9th 2009.
2. T. H. Institute, "Arrhythmia." http://www.texasheart.org/hic/ topics/cond/arrh ythmia.cfm. Updated June 2010.
3. Inan Guler, Elif Derya Ubeyli, ECG beat classifier designed by combined neural network model, Pattern Recognition, Volume 38, Issue 2, February 2005, Pages 199-208, ISSN 0031- 3203, DOI: 10.1016/j.patcog.2004.06.009.
4. Yeap, T.H.; Johnson, F.; Rachniowski, M.; , ECG Beat Classification By A Neural Network, Engineering in Medicine and Biology Society, 1990., Proceedings of the Twelfth Annual International Conference of the IEEE , vol., no., pp.1457-1458, 1-4 Nov 1990 doi:10.1109/IEMBS.1990.691837 (Pubitemid 21690295)
5. Ozbay, Y.; Karlik, B.;, A recognition of ECG arrhytihemias using artificial neural networks, Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE , vol.2, no., pp. 1680- 1683 vol.2, 2001 doi:10.1109/IEMBS.2001.1020538 (Pubitemid 35388931)
6. Liang-Yu Shyu; Ying-Hsuan Wu; Hu, W.;, Using wavelet transform and fuzzy neural network for VPC detection from the holter ECG, Biomedical Engineering, IEEE Transactions on , vol.51, no.7, pp.1269-1273, July 2004 doi:10.1109/TBME.2004.824131 (Pubitemid 38787932)
7. Ceylan, R. and zbay, Y. 2007. Comparison of FCM, PCA and WT techniques for classification ECG arrhythmias using artificial neural network. Expert Syst. Appl. 33, 2 (Aug. 2007),286-295. DOI=http://dx.doi.org/10.1016/j.eswa.2006.05. 014 (Pubitemid 46150036)
8. Elsayad, A.M.;, Classification of ECG arrhythmia using learn- ing vector quantization neural networks, Computer Engineering & Systems, 2009. ICCES 2009. International Conference on , vol., no., pp.139-144, 14-16 Dec. 2009 doi: 10.1109/IC- CES.2009.5383295
9. Karsten Sternickel, Automatic pattern recognition in ECG time series, Computer Methods and Programs in Biomedicine, Volume 68, Issue 2, May 2002, Pages 109-115, ISSN 0169-2607, DOI: 10.1016/S0169- 2607(01)00168-7. (Pubitemid 34257972)
10. Karraz, G.; Magenes, G.;, Automatic Classification of Heart- beats using Neural Network Classifier based on a Bayesian Framework, Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE , vol., no., pp.4016-4019, Aug. 30 2006-Sept. 3 2006 doi:10.1109/IEMBS.2006.259356 (Pubitemid 46520791)
11. B.Anuradha, V.C.Veera Reddy; Cardiac Arrhythmia Classification Using Fuzzy Classifiers, Journal of Theoretical and Applied Information Technology, 2008
12. Exarchos, T. P., Tsipouras, M. G., Exarchos, C. P., Papaloukas, C., Fotiadis, D. I., and Michalis, L. K. 2007. A methodology for the automated creation of fuzzy expert systems for ischaemic and arrhythmic beat classification based on a set of rules obtained by a decision tree. Artif. Intell. Med. 40, 3 (Jul. 2007), 187-200. DOI= http://dx.doi.org/10.1016/j. artmed.2007.04.001 (Pubitemid 47048715)
13. Yeh Y.-C., Wang W.-J., Chiou C.W.;, Heartbeat case determination using fuzzy logic method on ECG signals, International Journal of Fuzzy Systems, Vol. 11, No. 4, December 2009
14. Hao Zhang; Li-Qing Zhang; , ECG analysis based on PCA and Support Vector Machines, Neural Networks and Brain, 2005. ICNN&B '05. International Conference on , vol.2, no., pp.743-747, 13-15 Oct. 2005 doi: 10.1109/ICNNB. 2005.1614733 (Pubitemid 46289061)
15. Kampouraki, A.; Manis, G.; Nikou, C.; , Heartbeat Time Series Classification With Support Vector Machines, Information Technology in Biomedicine, IEEE Transactions on, vol.13, no.4, pp.512-518, July 2009 doi: 10.1109/TITB.2008.2003323
16. Nasiri, J.A.; Naghibzadeh, M.; Yazdi, H.S.; Naghibzadeh, B.;, ECG Arrhythmia Classification with Support Vector Machines and Genetic Algorithm, Computer Modeling and Simulation, 2009. EMS '09. Third UKSim European Symposium on, vol., no., pp.187- 192, 25-27 Nov. 2009 doi: 10.1109/EMS.2009.39
17. Melgani, F.; Bazi, Y.;, Classification of Electrocardiogram Signals With Support Vector Machines and Particle Swarm Optimization, Information Technology in Biomedicine, IEEE Transactions on , vol.12, no.5, pp.667-677, Sept. 2008 doi: 10.1109/TITB.2008.923147
18. Ghongade, R.; Ghatol, A.A.;, A brief performance evaluation of ECG feature extraction techniques for artificial neural network based classification, TENCON 2007 - 2007 IEEE Region 10 Conference , vol., no., pp.1-4, Oct. 30 2007-Nov. 2 2007 doi: 10.1109/TENCON.2007.4429096
19. Philip de Chazal; O'Dwyer, M.; Reilly, R.B.;, Automatic classification of heartbeats using ECG morphology and heartbeat interval features, Biomedical Engineering, IEEE Transactions on, vol.51, no.7, pp.1196-1206, July 2004 doi: 10.1109/TBME.2004.827359 (Pubitemid 38787925)
20. G. B. Moody, MIT-BIH Arrhythmia Database., http://physionet.org/ physiobank/database/html/ mitdbdir/mitdbdir.htm. May 1997.
21. C. Li, C. Zheng, and C. Tai, Detection of ecg characteristic points using wavelet transforms, Biomedical Engineering, IEEE Transactions on, vol. 42, pp. 21-28, jan. 1995.
22. Qibin Zhao; Liqing Zhang; , ECG Feature Extraction and Classification Using Wavelet Transform and Support Vector Machines, Neural Networks and Brain, 2005. ICNN&B '05. International Conference on, vol.2, no., pp.1089-1092, 13-15 Oct. 2005 doi: 10.1109/ICNNB.2005.1614807
23. J. W. Gardner, P. Boilot and E. L. Hines , Enhancing elec- tronic nose performance by sensor selection using a new integer- based genetic algorithm approach, Sensors and Actuators in press, 2004.
24. S. Haykin, Neural network, a comprehensive foundation, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 1999.
25. Paul E. Keller, Overview of electronic nose algorithms, IJCNN99, Washinton, DC, USA.
26. Kohonen, T., Improved vesion of learning vector quantization, Proc. of IEEE-IJCNN, 1990,I,545-550.
27. Fausett, L. Fundamental of Neural Network: architectures, algorithms, and applications. Prentice-Hall, New Jersey, 1994
28. Senhadji, L. and Carrault, G. and Bellanger, J.J. and Passariello, G, Comparing wavelet transforms for recognizing car- diac patterns, Engineering in Medicine and Biology Magazine IEEE, vol. 14, pp. 167173, 1995.
29. Kuncheva, Ludmila I.;, Combining Pattern Classifiers: Methods and Algorithms, Wiley- Interscience, 2004,p18-p20 ISBN:0471210781
30. Wisnu Jatmiko, T. Fukuda, F. Arai, and B. Kusumoputro, Artificial Odor Discrimination System Using Multiple Quartz Resonator Sensor and Various Neural Networks for Recognizing Fragrance Mixtures, IEEE Sensors Journal, vol. 6. no. 1, pp. 223-233, Feb. 2006. (Pubitemid 43131714)