Intelligent hybrid methods for ECG classification - A review

Journal of Medical and Biological Engineering

Volumn 28, Issue 1, 2008, Pages 1-10

  Shyu, Liang Yu ^a   Hu, Weichih ^a  

^a CHUNG YUAN CHRISTIAN UNIVERSITY   (Taiwan)

Author keywords

ECG classification; Hybrid system; Neural network

Indexed keywords

ALGORITHMS; FUZZY NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; WAVEFORM ANALYSIS;

ECG CLASSIFICATION; HYBRID METHODS; WAVEFORM CLASSIFICATION;

ELECTROCARDIOGRAPHY;

ALGORITHM; AMPLITUDE MODULATION; ARTIFICIAL NEURAL NETWORK; DECISION MAKING; ELECTROCARDIOGRAM; FUZZY SYSTEM; MATHEMATICAL COMPUTING; NORMAL DISTRIBUTION; REVIEW;

EID: 42949130110     PISSN: 16090985     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review

References (63)

1. B. U. Kohler, C. Hennig and R. Orglmeister, "The principles of software QRS detection," IEEE Eng. Med. Biol. Mag., 21: 42-57, 2002.
2. F. Cantini, M. Emdin, C. Passino, M. Varanini and F. Conforti, "Validation of a novel algorithm for ventricular repolarization analysis: use of Physionet resources," Comput. Cardiol., 30: 509-512, 2003.
3. Z. Dokur, T. Olmez and E. Yazgan, "Comparison of discrete wavelet and Fourier transforms for ECG beat classification," Electron. Lett., 35: 1502-1504, 1999.
4. Z. Dokur and T. Olmez, "ECG beat classification by a novel hybrid neural network," Comput. Meth. Programs Biomed., 66: 167-181, 2001.
5. S. Wu, Y. Qian, Z. Gao and J. Lin, "A novel method for beat-to-beat detection of ventricular late potentials," IEEE Trans. Biomed. Eng., 48: 931-935, 2001.
6. A. Tuzman, S. Chialanza, M. Acosta, R. Bartesaghi, T. Hobbins and A. Fonseca, "Best wavelet basis design for joint compression-classification of long ECG data records," Comput. Cardiol., 24: 287-290, 1997.
7. K. Sternickel, "Automatic pattern recognition in ECG time series," Comput. Meth. Programs Biomed., 68: 109-115, 2002.
8. I. Guler and E. D. Ubeyli, "Feature saliency using signal-to-noise ratios in automated diagnostic systems developed for ECG beats," Expert Syst. Appl., 28: 295-304, 2005.
9. A. S. Al-Fahoum and I. Howitt, "Combined wavelet transformation and radial basis neural networks for classifying life-threatening cardiac arrhythmias," Med. Biol. Eng. Comput., 37: 566-573, 1999.
10. V. Jain and J. S. Sahambi, "Neural network and wavelets in arrhythmia classification," Lect. Notes Comput. Sci., 3285: 92-99, 2004.
11. R. V. Andreao, B. Dorizzi, P. C. Cortez and J. C. M. Mota, "Efficient ECG multi-level wavelet classification through neural network dimensionality reduction," Proc. of the 12th IEEE Workshop on Neural Networks for Signal Processing, 395-404, 2002.
12. G. K. Prasad and J. S. Sahambi, "Classification of ECG arrhythmias using multi-resolution analysis and neural networks," Conf. on Convergent Technologies for Asia-Pacific Region, 1: 227-231, 2003.
13. A. Mousa and A. Yimaz, "Neural network detection of ventricular late potentials in ECG signals using wavelet transform extracted parameters," Proc. of the 23rd Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, 2: 1668-1671, 2001.
14. Y. H. Wu and L. Y. Shyu, "Detection of VPC using wavelet transform and fuzzy neural network," Proc. of the First Joint BMES/EMBS Conf., 2: 1200, 1999.
15. H. Dickhaus and H. Heinrich, "Identification of high risk patients in cardiology by wavelet networks," Proc. of the 18th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, 3: 923-924, 1996.
16. W. W. Dai, Z. Yang, S. L. Lim, O. Mikhailova and J. Chee, "Processing and analysis of ECG signal using nonorthogonal wavelet transform," Proc. of the 20th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, 1: 139-142, 1998.
17. J. Yao, Q. Gan, X. D. Zhang and J. Li, "Pruning algorithm in wavelet neural network for ECG signal classification," Proc. of the 20th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, 3: 1482-1485, 1998.
18. R. Carranza and D. Andina, "Wavelet-neural processing for computer aided diagnosis," Proc. of the 5th Biannual World Automation Congress, 13: 215-220, 2002.
19. M. Ogawa, Y. Kimura, T. Tamura and T. Togawa, "Fully automated ECG data acquisition in a bathtub," Proc. of the 18th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, 1: 55-56, 1996.
20. D. Frenkel and J. Nadal, "Ischemic episode detection using an artificial neural network trained with isolated ST-T segments," Comput. Cardiol., 26: 53-56, 1999.
21. W. Ye, G. Li, L. Lin and Q. Yu, "ECG analysis based on PCA and SOM," Proc. of the 2003 Int. Conf. on Neural Networks and Signal Processing, 1: 37-40, 2003.
22. F. Vargas, D. Lettnin, M. C. F. de Castro and M. Macarthy, "Electrocardiogram pattern recognition by means of MLP network and PCA: a case study on equal amount of input signal types," Proc. of VII Brazilian Symp. on Neural Networks, 200-205, 2002.
23. C. Papaloukas, D. I. Fotiadis, A. Likas and L. K. Michalis, "An ischemia detection method based on artificial neural networks," Artif. Intell. Med., 24: 167-178, 2002.
24. Z. Wang, Z. He and J. Z. Chen, "Blind EGG separation using ICA neural networks," Proc. of the 19th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, 3: 1351-1354, 1997.
25. S. Osowski and T. H. Linh, "ECG beat recognition using fuzzy hybrid neural network," IEEE Trans. Biomed. Eng., 48: 1265-1271, 2001.
26. R. Silipo, G. Bortolan and C. Marchesi, "Fuzzy preprocessing and artificial neural network classification for the diagnostic interpretation of the resting ECG," Comput. Cardiol., 365-368, 1995.
27. H. L. Lu, K. Ong and P. Chia, "An automated ECG classification system based on a neuro-fuzzy system," Comput. Cardiol., 387-390, 2000.
28. Y. Wang, Y. S. Zhu, N. V. Thakor and Y H. Xu, "A short-time multifractal approach for arrhythmia detection based on fuzzy neural network," IEEE Trans. Biomed. Eng., 48: 989-995, 2001.
29. P. Bozzola, G. Bortolan, C. Combi, F. Pinciroli and C. Brohet, "A hybrid neuro-fuzzy system for ECG classification of myocardial infarction," Comput. Cardiol., 241-244, 1996.
30. I. Guler and E. D. Ubeyli, "Application of adaptive neuro-fuzzy inference system for detection of electrocardiographic changes in patients with partial epilepsy using feature extraction," Expert Syst. Appl., 27: 323-330, 2004.
31. M. Engin, "ECG beat classification using neuro-fuzzy network," Pattern Recognit. Lett., 25: 1715-1722, 2004.
32. T. H. Linh, S. Osowski and M. Stodolski, "On-line heart beat recognition using hermite polynomials and neuro-fuzzy network," IEEE Trans. Instrum. Meas., 52: 1224-1231, 2003.
33. S. Osowski and T. H. Linh, "Fuzzy clustering neural network for classification of ECG beats," Proc. of the IEEE-INNS-ENNS Int. Joint Conf. on Neural Networks, 5: 26-30, 2000.
34. Z. X. Xie, H. Z. Xie and X. B. Ning, "Application of fuzzy neural network to ECG diagnosis," Int. Conf. on Neural Networks, 1: 62-66, 1997.
35. S. Osowski and T. H. Linh, "Analysis of features for efficient ECG signal classification using neuro-fuzzy network," Proc. IEEE Int. Joint Conf. on Neural Networks, 3: 2443-2448, 2004.
36. H. Dickhaus and H. Heinrich, "Classifying biosignals with wavelet networks," IEEE Eng. Med. Biol. Mag., 15: 103-111, 1996.
37. R. K. Galvao and T. Yoneyama, "Improving the discriminatory capabilities of a neural classifier by using a biased-wavelet layer," Int. J. Neural Syst., 9: 167-174, 1999.
38. F. M. Ham and S. Han, "Classification of cardiac arrhythmias using fuzzy ARTMAP," IEEE Trans. Biomed. Eng., 43: 425-430, 1996.
39. M. B. Tumer, L. A. Belfore and K. M. Ropella, "A syntactic methodology for automatic diagnosis by analysis of continuous time measurements using hierarchical signal representations," IEEE Trans. Syst. Man Cybern. Part B-Cybern., 33: 951-965, 2003.
40. T. Stamkopoulos, K. Diamantaras, N. Maglaveras and M. Strintzis, "ECG analysis using nonlinear PCA neural networks for ischemia detection," IEEE Trans. Signal Process., 46: 3058-3067, 1998.
41. C. K. S. Vijila, S. Renganathan and S. Johnson, "Suppression of maternal ECG from fetal ECG using neuro fuzzy logic technique," Proc. of the Int. Joint Conf. on Neural Networks, 2: 1007-1012, 2003.
42. Z. S. Wang and J. D. Z. Chen, "Robust ECG R-R wave detection using evolutionary-programming-based fuzzy inference system (EPFIS), and application to assessing brain-gut interaction," IEE Proc.-Sci. Meas. Technol., 147: 351-356, 2000.
43. T. Domider, E. J. Tkacz, P. Kostka and A. Wrzesniowski, "A new approach to the P-wave detection and classification based upon application of wavelet neural network," Proc. of the 23rd Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, 2: 1758-1760, 2001.
44. V. Pilla, Jr. and H. S. Lopes, "Evolutionary training of a neurofuzzy network for detection of P wave of the ECG," Proc. of 3rd Int. Conf. on Computational Intelligence and Multimedia Applications, 102-106, 1999.
45. W. A. Sandham, D. C. Thomson and D. J. Hamilton, "ECG compression using artificial neural networks," Proc. of IEEE 17th Annual Conf. on Engineering in Medicine and Biology Society, 1: 193-194, 1995.
46. S. M. Ahmeda and M. Abo-Zahhad, "A new hybrid algorithm for ECG signal compression based on the wavelet transformation of the linearly predicted error," Med. Eng. Phys., 23: 117-126, 2001.
47. R. Silipo, G. Bortolan and C. Marchesi, "Design of hybrid architectures based on neural classifier and RBF pre-processing for ECG analysis," Int. J. Approx. Reasoning, 21: 177-196, 1999.
48. L. Y. Shyu, Y. H. Wu and W. Hu, "Using wavelet transform and fuzzy neural network for VPC detection from the Holter ECG," IEEE Trans. Biomed. Eng., 51: 1269-1273, 2004.
49. F. Hoppner, F. Klawonn, R. Kruse and T. Runkler, Fuzzy Cluster Analysis, Methods for Classification, Data Analysis and Image Recognition, New York: John Wiley & Sons, 1999.
50. 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: 2507-2515, 2006.
51. C. Li, C. Zheng and C. Tai, "Detection of ECG characteristic points using wavelet transforms," IEEE Trans. Biomed. Eng., 42: 21-28, 1995.
52. B. Castro, D. Kogan and A. B. Geva, "ECG feature extraction using optimal mother wavelet," The 21st IEEE Convention of the Electrical and Electronic Engineers in Israel, 346-350, 2000.
53. J. S. Sahambi, S. N. Tandon and R. K. P. Bhatt, "Using wavelet transforms for ECG characterization: an on-line digital signal processing system," IEEE Eng. Med. Biol. Mag., 16: 77-83, 1997.
54. L. Senhadji, G. Carrault, J. J. Bellanger and G. Passariello, "Comparing wavelet transforms for recognizing cardiac patterns," IEEE Eng. Med. Biol. Mag., 14: 167-173, 1995.
55. I. Guler and E. D. Ubeyli, "ECG beat classifier designed by combined neural network model," Pattern Recognit., 38: 199-208, 2005.
56. Available: http://www.efunda.com/math/Hermite/index.cfm
57. G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds and D. B. Rosen, "Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps," IEEE Trans. Neural Netw., 3: 698-713, 1992.
58. G. A. Carpenter, S. Grossberg and D. B. Rosen, "Fuzzy ART: fast stable learning and categorization of analog patterns by an adaptive resonance system," Neural Netw., 4: 759-771, 1991.
59. M. A. Kramer, "Nonlinear principal component analysis using autoassociative neural networks," AICHE J., 37: 233-243, 1991.
60. K. I. Diamantaras and S. Y. Kung, Principal Component Neural Networks: Theory and Applications, New York: John Wiley & Sons, 1996.
61. J. Zhou, "Automatic detection of premature ventricular contraction using quantum neural networks," Proc. Third IEEE Symp. on Bioinformatics and Bioengineering, 169-173, 2003.
62. G. A. Carpenter and S. Grossberg, "A massively parallel architecture for a self-organizing neural pattern recognition machine," Comput. Vis. Graph. Image Process., 37: 54-115, 1987.
63. G. Bortolan, I. Jekova and I. Christov, "Comparison of four methods for premature ventricular contraction and normal beat clustering," Comput. Cardiol., 32: 921-924, 2005.