Noise-tolerant electrocardiogram beat classification based on higher order statistics of subband components

Artificial Intelligence in Medicine

Volumn 46, Issue 2, 2009, Pages 165-178

  Yu, Sung Nien ^a   Chen, Ying Hsiang ^a  

^a NATIONAL CHUNG CHENG UNIVERSITY   (Taiwan)

Author keywords

Discrete wavelet transform; Electrocardiogram; Feature selection; Higher order statistics; Noise tolerant

Indexed keywords

BEAT CLASSIFICATIONS; CORRELATION COEFFICIENTS; DISCRETE-WAVELET-TRANSFORM; DISCRIMINATION RATES; ELECTROCARDIOGRAM; ENVIRONMENTAL NOISE; FEATURE DIMENSIONS; FEATURE SELECTION; FEATURE SELECTION ALGORITHMS; FEATURE SELECTION METHODS; FEATURE SETS; FEEDFORWARD BACKPROPAGATION NEURAL NETWORKS; HIGHER ORDER STATISTICS; NOISE ARTIFACTS; NOISE-TOLERANT; R-R INTERVALS; REDUNDANT FEATURES; SAMPLE SELECTIONS; SIGNAL TO NOISE; SUB BANDS;

AUDIO SYSTEMS; DISCRETE WAVELET TRANSFORMS; ELECTROCARDIOGRAPHY; ELECTROCHROMIC DEVICES; NEURAL NETWORKS; SIGNAL ANALYSIS; SIGNAL PROCESSING; SIGNAL TO NOISE RATIO;

REGRESSION ANALYSIS;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; ELECTROCARDIOGRAM; HEART BEAT; NOISE REDUCTION; PRIORITY JOURNAL; SAMPLING; SIGNAL DETECTION; SIGNAL NOISE RATIO; STATISTICAL ANALYSIS; WHITE NOISE;

ALGORITHMS; ELECTROCARDIOGRAPHY; SENSITIVITY AND SPECIFICITY;

EID: 67349217457     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2008.11.004     Document Type: Article

References (36)

1. Jekova I., Bortolan G., and Christov I. Assessment and comparison of different methods for heartbeat classification. Med Eng Phys 30 (2008) 248-257
2. Chen S.W. Complexity-measure-based sequential hypothesis testing for real-time detection of lethal cardiac arrhythmias. EURASIP J Adv Signal Process (2007) 1-8
3. Hosseini H.G., Luo D., and Reynolds K.J. The comparison of different feed forward neural network architectures for ECG signal diagnosis. Med Eng Phys 28 (2006) 372-378
4. Christov I., Gomez-Herrero G., Krasteva V., Jekova I., Gotchev A., and Egiazarian K. Comparative study of morphological and time-frequency ECG descriptors for heartbeat classification. Med Eng Phys 28 (2006) 876-887
5. Tsipouras M.G., Fotiadis D.I., and Sideris D. An arrhythmia classification system based on the RR-interval signal. Artif Intell Med 33 (2005) 237-250
6. Khadra L., Al-Fahoum A.S., and Binajjaj S. A quantitative analysis approach for cardiac arrhythmia classification using higher order spectral techniques. IEEE Trans Biomed Eng 52 (2005) 1840-1845
7. Ubeyli E.D. ECG beats classification using multiclass support vector machines with error correcting output codes. Digit Signal Prog 17 (2007) 675-684
8. Yu S.N., and Chen Y.H. Electrocardiogram beat classification based on wavelet transformation and probabilistic neural network. Pattern Recognit Lett 28 (2007) 1142-1150
9. Krishna Prasad G., and Sahambi J.S. Classification of EGG arrhythmias using multi-resolution analysis and neural networks. In: Khincha H.P. (Ed). IEEE TENCON 2003: Confernce on Covergent Technologies for the Asia-Pacific Region (2003), Allied Publishers Pvt. Ltd., New Delhi 227-231
10. Osowski S., and Linh T.H. ECG beat recognition using fuzzy hybrid neural network. IEEE Trans Biomed Eng 48 (2001) 1265-1271
11. Osowski S., Hoai L.T., and Markiewicz T. Support vector machine-based expert system for reliable heartbeat recognition. IEEE Trans Biomed Eng 51 (2004) 582-589
12. Jiang W., and Kong S.G. Block-based neural networks for personalized ECG signal classification. IEEE Trans Neural Netw 18 (2007) 1750-1761
13. Lagerholm M., Peterson C., Braccini G., Edenbrandt L., and Sornmo L. Clustering ECG complexes using Hermite functions and self-organizing maps. IEEE Trans Biomed Eng 47 (2000) 838-848
14. Polat K., and Gunes S. Detection of ECG arrhythmia using a differential expert system approach based on principal component analysis and least square support vector machine. Appl Math Comput 186 (2007) 898-906
15. Guler I., and Ubeyli E.D. A modified mixture of experts network structure for ECG beats classification with diverse features. Eng Appl Artif Intell 18 (2005) 845-856
16. Engin M. ECG beat classification using neuro-fuzzy network. Pattern Recognit Lett 25 (2004) 1715-1722
17. Jakubowski J., Kwiatos K., Chwaleba A., and Osowski S. Higher order statistics and neural network for tremor recognition. IEEE Trans Biomed Eng 49 (2002) 152-159
18. Martinez J.P., Almeida R., Olmos S., Rocha A.P., and Laguna P. A wavelet-based ECG delineator: evaluation on standard databases. IEEE Trans Biomed Eng 51 (2004) 570-581
19. Sahambi J.S., Tandon S.N., and Bhatt R.K.P. Using wavelet transforms for ECG characterization-an on-line digital signal processing system. IEEE Eng Med Biol Mag 16 (1997) 77-83
20. Fleuret F. Fast binary feature selection with conditional mutual information. J Mach Learn Res 5 (2004) 1531-1555
21. Yu L., and Liu H. Feature selection for high-dimensional data: a fast correlation-based filter solution. In: Fawcett T., and Mishra N. (Eds). Proceedings of The Twentieth International Conference on Machine Leaning (ICML-2003) (2003), AAAI Press, Menlo Park, California
22. Battiti R. Using mutual information for selecting features in supervised neural-net learning. IEEE Trans Neural Netw 5 (1994) 537-550
23. Physiobank Archieve Index, MIT-BIH Arrhythmia Database: http://www.physionet.org/physiobank/database/mitdb/ [accessed: 29 June, 2008].
24. Physiobank Archieve Index, Sleep Heart Health Study Polysomnography Database: http://www.physionet.org/physiobank/database/shhpsgdb/ [accessed: 29 June, 2008].
25. Physiobank Archieve Index, MIT-BIH Noise Stress Test Database: http://www.physionet.org/physiobank/database/nstdb/ [accessed: 29 June, 2008].
26. Duda R.O., Hart P.E., and Stork D.G. Pattern classification (2000), Wiley, New York, NY pp. 117-124
27. Hu Y.H., Palreddy S., and Tompkins W.J. A patient-adaptable ECG beat classifier using a mixture of experts approach. IEEE Trans Biomed Eng 44 (1997) 891-900
28. Ham F.M., and Han S. Classification of cardiac arrhythmias using fuzzy ARTMAP. IEEE Trans Biomed Eng 43 (1996) 425-429
29. Haykin S. Neural networks: a comprehensive foundation (1994), Prentice-Hall, Englewood Cliffs, NJ pp. 138-153
30. Dash P.K. Electrocardiogram monitoring. Indian J Anaesth 46 (2002) 251-260
31. Daqrouq K. ECG baseline wandering reduction using discrete wavelet transform. Asian J Inf Technol 4 (2005) 989-995
32. Boucheham B., Ferdi Y., and Batouche M.C. Piecewise linear correction of ECG baseline wander: a curve simplification approach. Comput Meth Programs Biomed 78 (2005) 1-10
33. Van Alste J.A., and Schilder T.S. Removal of base-line wander and power-line interference from the ECG by an efficient FIR filter with a reduced number of taps. IEEE Trans Biomed Eng 32 (1985) 1052-1060
34. Martens S.M.M., Mischi M., Oei S.G., and Bergmans J.W.M. An improved adaptive power line interference canceller for electrocardiography. IEEE Trans Biomed Eng 53 (2006) 2220-2231
35. Vaidyanathan P.P. Multirate systems and filter banks (1992), Prentice-Hall, Englewood Cliffs, NJ pp. 109-111
36. Quan S.F., Howard B.V., Iber C., Kiley J.P., Nieto F.J., O'Connor G.T., et al. The sleep heart health study: design, rationale, and methods. Sleep 20 (1997) 1077-1085