SVM based methods for arrhythmia classification in ECG

2010 International Conference on Computer and Communication Technology, ICCCT-2010

Volumn , Issue , 2010, Pages 486-490

  Kohli, Narendra ^a   Verma, Nishchal K ^a   Roy, Abhishek ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

^b NATIONAL INSTITUTE OF TECHNOLOGY KARNATAKA   (India)

Author keywords

Arrhythmias; Classification; Electrocardiogram; Support vector machine

Indexed keywords

ACCURACY RATE; ARRHYTHMIA CLASSIFICATION; ARRHYTHMIAS; CARDIAC ARRHYTHMIA; CLASSIFICATION; COMPLEX NATURE; CORONARY ARTERY DISEASE; DATA SETS; ELECTROCARDIOGRAM; FUZZY DECISION; HEART BEATS; MYOCARDIAL INFARCTION; ONE-AGAINST-ALL METHODS; SVM CLASSIFIERS; SVM-BASED METHODS; UNIVERSITY OF CALIFORNIA;

DISEASES; ELECTROCARDIOGRAPHY; ELECTROCHROMIC DEVICES; HEART; SUPPORT VECTOR MACHINES;

CLASSIFICATION (OF INFORMATION);

EID: 78650538842     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCCT.2010.5640480     Document Type: Conference Paper

References (18)

1. rd Annual conference, IEEE/EMBS, Oct. 25-28, 2001, Istanbul, Turkey.
2. B. Anuradha and V.C. Veera Reddy, "Cardiac Arrhythmia Classification Using Fuzzy Classifier," Journal of Theoretical and Applied Information Technology.
3. th October 2009, 8:31.
4. M.H. Song, J.Lee, S.P. Cho, K.J. Lee, and S.K. Yoo, "Support Vector Machine Based Arrhythmia Classification Using Reduced Features," International Journal of Control, Automation, and Systems, vol. 3, no. 4, pp. 571-579, Dec. 2005.
5. B. Devine and P. W. Macfarlane, "Detection of Electrocardiographic left ventricular strain using neural nets," Med. Biol. Eng. Comput, 31, pp. 343-348, 1993.
6. Y. H. Hu, W. J. Tompkins, J. L. Urristi, and X. A. Valtino, "Application of artificial neural networks for ECG signal detection and classification," Journal of Electrocardiology, 26, pp. 66-73, 1993.
7. R. Silipo, G. Bortolan, and C. Marchesi, "Supervised and unsupervised learning for diagnostic ECG classification," IEEE Eng. in Medicine & Biology, pp.1054, 31 Oct.-3 Nov., Amsterdam, The Netherlands, 1996.
8. Sugiura, T. Hirata, H. Harada, Y. and Kazui, T., "Automatic discrimination of arrhythmia waveforms using fuzzy logic", Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 20, no. 1, 1998.
9. Acharya U R, Subbanna Bhat P, Iyengar S S, Rao A and Dua S, "Classification of heart rate using artificial neural network and fuzzy equivalence relation", Pattern Recognit., vol. 36, pp. 61-68, 2003.
10. B. Liu, Z. Hao, and E.C.C. Tsang, "Nesting One-Against-One Algorithm Based on SVM's for Pattern Classification," IEEE Transactions on Neural Networks, Vol. 19, No. 12, Dec. 2008.
11. V. N. Vapnik, The Nature of Statistical Learning Theory. London, U.K.: Springer-Verlag, 1995.
12. M. Aizeman, E. Braverman, and L. Rozonoer, "Theoretical foundations of potential function method in pattern recognition learning," Autom. Remote Control, vol. 25, pp. 821-837, 1964.
13. S. Saitoh, Theory of Reproducing Kernels and Its Applications. Harlow, U.K.: Longman, 1988.
14. S. Abe, Support Vector Machines for Pattern Classification. London, U.K.: Springer-Verlag, 2006.
15. U. H. G. Kreßel, "Pairwise classification and support vector machines," in Advances in Kernel Methods-Support Vector Learning, B. Schölkopf, C. Burges, and A. Smola, Eds. Cambridge, MA: MIT Press, 1998, pp. 255-268.
16. D. Tsujinishi and S. Abe, "Fuzzy least squares support vector machines for multiclass problems," Neural Netw., vol. 16, pp. 785-792, 2003.
17. R. Debnath, N. Takahide, and H. Takahashi, "A decision based one-against-one method for multi-class support vector machine," Pattern Anal. Appl., vol. 7, pp. 164-175, 2004.
18. P. M. Murphy and D. W. Aha, UCI Machine Learning Repository Database, 2010 [Online]. Available: [http://archive.ics.uci.edu/ml], Irvine, CA: University of California, School of Information and Computer Science.