Detection of electrocardiogram signals using an efficient method

Applied Soft Computing Journal

Volumn 22, Issue , 2014, Pages 108-117

  Ebrahimzadeh, A ^a   Shakiba, B ^a   Khazaee, A ^a  

^a BABOL NOSHIRVANI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Bees algorithm; ECG beat classification; Higher order statistics; Radial basis function neural network

Indexed keywords

CLASSIFICATION (OF INFORMATION); DIAGNOSIS; DISEASES; FEATURE EXTRACTION; HIGHER ORDER STATISTICS; IMAGE SEGMENTATION; RADIAL BASIS FUNCTION NETWORKS; SIGNAL DETECTION;

ATRIAL PREMATURE CONTRACTION; BEES ALGORITHMS; CLASSIFICATION ACCURACY; ECG BEAT CLASSIFICATIONS; ELECTROCARDIOGRAM SIGNAL; PREMATURE VENTRICULAR CONTRACTION; RADIAL BASIS FUNCTION NEURAL NETWORKS; STATIONARY WAVELET TRANSFORMS;

ELECTROCARDIOGRAPHY;

EID: 84901999931     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2014.05.003     Document Type: Article

References (42)

1. H.M. Rai, A. Trivedi, and S. Shukla ECG signal processing for abnormalities detection using multi-resolution wavelet transform and Artificial Neural Network classifier Measurement 46 2013 3238 3246
2. P.C. Chang, J.J. Lin, J.C. Hsieh, and J. Weng Myocardial infarction classification with multi-lead ECG using hidden Markov models and Gaussian mixture models Appl. Soft Comput. 12 2012 3165 3175
3. Z. Zidelmal, A. Amirou, D. Ould-Abdeslamb, and J. Merckle ECG beat classification using a cost sensitive classifier Comput. Methods Programs Biomed. 111 2013 570 577
4. H. GholamHosseini, D. Luob, and K.J. Reynolds The comparison of different feed forward neural network architectures for ECG signal diagnosis Med. Eng. Phys. 28 2006 372 378
5. G. Ranganathan, R. Rangarajan, and V. Bindhu Estimation of heart rate signals for mental stress assessment using neuro fuzzy technique Appl. Soft Comput. 12 2012 1978 1984
6. F. Melgani, and Y. Bazi Classification of Electrocardiogram Signals With Support Vector Machines and Particle Swarm Optimization, 12 2008 667 677
7. B. Mohammadzadeh Asl, S.K. Setarehdan, and M. Mohebbi Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal Artif. Intell. Med. 44 2008 51 64
8. B. Dogan, and M. Korurek A new ECG beat clustering method based on kernelized fuzzy c-means and hybrid ant colony optimization for continuous domains Appl. Soft Comput. 12 2012 3442 3451
9. D. Gaetano, S. Panunzi, F. Rinaldi, A. Risi, and M. Sciandrone A patient adaptable ECG beat classifier based on neural networks Appl. Math. Comput. 213 2009 243 249
10. S.N. Yu, and K. Chou Selection of significant independent components for ECG beat classification Expert Syst. Appl. 36 2009 2088 2096
11. A. Ebrahimzadeh, and A. Khazaee Detection of premature ventricular contractions using MLP neural networks: a comparative study Measurement 43 2010 103 112
12. A. Ebrahim Zadeh, A. Khazaee, and V. Ranaee Classification of the electrocardiogram signals using supervised classifiers and efficient features Comput. Methods Programs Biomed. 99 2010 179 194
13. M. Llamedo, and J.P. Martínez Heartbeat classification using feature selection driven by database generalization criteria Biomed. Eng., IEEE Trans. 58 2011 616 625
14. S. Kiranyaz, T. Ince, J. Pulkkinen, and M. Gabbouj Personalized long-term ECG classification: a systematic approach Expert Syst. Appl. 38 2011 3220 3226
15. Y. Kutlu, and D. Kuntalp A multi-stage automatic arrhythmia recognition and classification system Comput. Biol. Med. 41 2011 37 45
16. Lanatá, G. Valenza, C. Mancuso, and E.P. Scilingo Robust multiple cardiac arrhythmia detection through bispectrum analysis Expert Syst. Appl. 38 2011 6798 6804
17. S. Osowski, K. Siwek, and R. Siroic Neural system for heartbeats recognition using genetically integrated ensemble of classifiers Comput. Biol. Med. 41 2011 173 180
18. Y.H. Chen, and S. Yu Selection of effective features for ECG beat recognition based on nonlinear correlations Artif. Intell. Med. 54 2012 43 52
19. Y. Kutlua, and D. Kuntalp Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients Comput. Methods Programs Biomed. 105 2012 257 267
20. M. Kania, M. Fereniec, and R. Maniewski Wavelet denoising for multilead high resolution ECG signals Meas. Sci. Rev. 7 4 2007 (Section 2)
21. D. Donoho, and I. Johnstone Adapting to unknown smoothness via wavelet shrinkage J. ASA 90 1995 1200 1223
22. G. Nason, and B. Silverman The stationary wavelet transform and some Statistical applications, Wavelets and Statistics Springer Lecture Notes in Statistics 103 1995 Springer-Verlag New York 281 300
23. A. Savitzky, and M.J.E. Golay Smoothing and differentiation of data by simplified least squares procedures Anal. Chem. 36 1964 1627 1639
24. R.J. Martis, U.R. Acharya, K. Ray, and C. Chakraborty Application of higher order cumulants to ECG signals for the cardiac health diagnosis 33rd Annual International Conference of the IEEE EMBS Boston August 30-September 3, MA, USA 2011
25. A. Ebrahimzadeh, and A. Khazaee An efficient technique for classification of electrocardiogram signals Adv. Elect. Comput. Eng. 9 2009 89 93
26. D.S. Broomhead, and D. Lowe Multivariable functional interpolation and adaptive networks Complex Syst. 2 1988 321 355
27. J. Moody, and C.J. Darken Fast learning in networks of locally-tuned processing units Neural Comput. 1 1989 281 294
28. U. Halici ANN EE543, METU EEE, ANKARA 2005 139 147
29. D.T. Pham, A. Ghanbarzadeh, E. Koc, S. Otri, S. Rahim, and M. Zaidi The Bees Algorithm. Technical Note 2005 Manufacturing Engineering Centre, Cardiff University UK
30. Duc Truong Pham, Ashraf Afify, EbubekirKoc, Manufacturing cell formation using the Bees Algorithm. IPROMS 2007 Innovative Production Machines and Systems Virtual Conference, Cardiff, UK.
31. D.T. Pham, E. Koç, J.Y. Lee, and J. Phrueksanant Using the Bees algorithm to schedule jobs for a machine Proc Eighth International Conference on Laser Metrology, CMM and Machine Tool Performance 2007 LAMDAMAP, Euspen UK, Cardiff 430 439
32. D.T. Pham, A. Ghanbarzadeh, E. Koç, S. Otri, S. Rahim, M. Zaidi, The Bees algorithm - a novel tool for complex optimisation problems, Proceedings of IPROMS 2006 Conference, 454-456.
33. R. Marknd, and G. Moody MIT-BIH Arrhythmia Database 1997 Available at: http://ecg.mit.edu/binfo.html
34. G.B. Moody, and R.G. Mark The impact of the mit/bih arrhythmia database IEEE Eng. Med. Biol. Mag. 20 2001 45 50
35. A. Khazaee, and A. Ebrahimzadeh Classification of electrocardiogram signals with support vector machines and genetic algorithms using power spectral features Biomed. Signal Process. Control 5 2010 252 263
36. K.C. Chua, V. Chandran, R. Acharya, and C.M. Lim Application of higher order statistics/spectra in biomedical signals: a review Med. Eng. Phys. 32 2010 679 689
37. S. Osowski, and T.H. Linh ECG beat recognition using fuzzy hybrid neural network IEEE Trans. Biomed. Eng. 48 2001 1265 1271 (Pubitemid 32988567)
38. H. Demuth, and M. Beale Neural Network Toolbox User's Guide 1997 The Mathworks, Inc. USA
39. O.T. Inan, L. Giovangrandi, and G.T.A. Kovacs Robust neural-network-based classification of premature ventricular contractions using wavelet transform and timing interval features IEEE. Trans. Biomed. Eng. 53 2006 2507 2515 (Pubitemid 46019538)
40. A. Ebrahimzadeh, and A. Khazaee High efficient system for Automatic Classification of the Electrocardiogram Beats Ann. Biomed. Eng. 39 2011 996 1011
41. I. Guler, and E.D. Ubeyli ECG beat classifier designed by combined neural network model Pattern Recognit. 38 2005 199 208
42. O. Michael Sensory Evaluation of Food: Statistical Methods and Procedures 1986 CRC Press Boca Raton, Florida 0-824-77337-3 487