Robust electrocardiogram (ECG) beat classification using discrete wavelet transform

Physiological Measurement

Volumn 29, Issue 5, 2008, Pages 555-570

  Minhas, Fayyaz Ul Amir Afsar ^a   Arif, Muhammad ^a  

^a PAKISTAN INSTITUTE OF ENGINEERING AND APPLIED SCIENCES   (Pakistan)

Author keywords

Beat classification; ECG; Principal component analysis (PCA); Wavelet transform

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; CLASSIFICATION (OF INFORMATION); DISCRETE WAVELET TRANSFORMS; EXTRACTION; FEATURE EXTRACTION; PRINCIPAL COMPONENT ANALYSIS; SIGNAL TO NOISE RATIO;

% REDUCTIONS; BEAT CLASSIFICATION; CLASSIFICATION ACCURACY; DISCRETE-WAVELET-TRANSFORM; FEATURES EXTRACTION; PRINCIPAL COMPONENT ANALYSE; PRINCIPAL-COMPONENT ANALYSIS; QRS COMPLEXES; ROBUST TECHNIQUE; WAVELETS TRANSFORM;

ELECTROCARDIOGRAPHY;

ANALYZER; ARTICLE; ECG ANALYZER; ELECTROCARDIOGRAM; HEART BEAT; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; QRS COMPLEX; RR INTERVAL;

EID: 45749119160     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/29/5/003     Document Type: Article

References (32)

1. Addison P S et al 2000 A novel wavelet based analysis reveals hidden structure in ventricular fibrillation IEEE Eng. Med. Biol. 19 383-92
2. Afonso V X 1995 ECG QRS detection Biomedical Digital Signal Processing ed W J Tompkins (Englewood Cliffs, NJ: Prentice-Hall)
3. Afonso V X et al 1997 Filter bank-based ECG beat classification Engineering in Medicine and Biology Society Proc. 19th Annual Int. Conf. IEEE
4. Al-Fahoum A S 1999 IH combined wavelet transform and radial basis neural networks for the classifying life threatening cardiac arrhythmias Med. Bio. Eng. Comput. 37 566-73
5. Alpaydin E 2005 Introduction to Machine Learning (Englewood Cliffs, NJ: Prentice-Hall)
6. Bortolan G et al 2005 Comparison of four methods for premature ventricular contraction and normal beat clustering Computers in Cardiology pp 921-4
7. Chen Y-H and Yu S N 2007 Subband features based on higher order statistics for ECG beat classification 29th Annual Int. Conf. IEEE Eng. Med. Biol. Soc. (Lyon, France)
8. Christov I, Jekova I and Bortolan G 2005 Premature ventricular contraction classification by the Kth nearest-neighbours rule Physiol. Meas. 26 123-30
9. Clifford G D 2006 ECG Statistics, noise, artifacts and missing data Advanced Methods and Tools for ECG Analysis ed G D Clifford, F Azuaje and P McSharry (London: Artech House)
10. Cohen A and Kovacevic J 1996 Wavelets: the mathematical background Proc. IEEE 84 514-22
11. Dokur Z, Olmez T and Yazgan E 1999 Comparison of discrete wavelet and Fourier transforms for ECG beat classification Electron. Lett. 35 1502-4
12. Engin M 2004 ECG beat classification using neuro-fuzzy network Pattern Recognit. Lett. 25 1715-22
13. Exarchos T P et al 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. 40 187-200
14. Güler İ and Übeyli E D 2005a A modified mixture of experts network structure for ECG beats classification with diverse features Eng. Appl. Artif. Intell. 18 845-56
15. Güler İ and Übeyli E D 2005b ECG beat classifier designed by combined neural network model Pattern Recognit. 38 199-208
16. Gutierrez A, Hernandez P, Lara M and Perez S 1998 A QRS detection algorithm based on Haar wavelet Computers in Cardiology 1998 (13-16 September 1998) pp 353-6
17. Houghton A R and Gary D 2003 Making Sense of the ECG: A Hands-on Guide (London: Arnold)
18. Inan O T, Giovangrandi L and Kovacs G T A 2006 Robust neural-network-based classification of premature ventricular contractions using wavelet transform and timing interval features IEEE Trans. Biomed. Eng. 53 2507-15
19. Kohler B U, Hennig C and Orglmeister R 2002 The principles of software QRS detection IEEE Eng. Med. Biol. Mag. 21 42-57
20. Li C, Zheng C and Tai C 1995 Detection of ECG characteristic points using wavelet transforms IEEE Trans. Biomed. Eng. 42 21-8
21. Mallat S and Zhong S 1992 Characterization of signals from multiscale edges IEEE Trans. Pattern Anal. Mach. Intell. 14 710-32
22. Mark R and Moody G 1988 MIT-BIH Arrhythmia Database Directory (Cambridge, MA: MIT Press)
23. Martinez J P et al 2004 A wavelet-based ECG delineator: evaluation on standard databases IEEE Trans. Biomed. Eng. 51 570-81
24. Minami K, Nakajima H and Toyoshima T 1999 Real-time discrimination of ventricular tachyarrhythmia with Fourier-transform neural network IEEE Trans. Biomed. Eng. 46 179-85
25. Niwas S I, Kumari R S S and Sadasivam V 2005 Artificial neural network based automatic cardiac abnormalities classification 6th Int. Conf. Computational Intelligence and Multimedia Applications (16-18 August 2005) pp 41-6
26. Osowski S and Tran Hoai L 2001 ECG beat recognition using fuzzy hybrid neural network IEEE Trans. Biomed. Eng. 48 1265-71
27. Prasad G K and Sahambi J S 2003 Classification of ECG arrhythmias using multiresolution analysis and neural networks Conf. Convergent Technologies Bangalore, India
28. Proakis J G and Manolakis M G 1999 Digital Signal Processing: Principles, Algorithms, and Applications (Englewoods Cliffs, NJ: Prentice-Hall)
29. Reisner A T, Clifford G D and Mark R G 2006 The physiological basis of the electrocardiogram Advanced Methods and Tools for ECG Data Analysis ed G D Clifford, F Azuaje and P E McSharry (Boston, MA: Artech House)
30. Sung-Nien Y and Kuan-To C 2007 A switchable scheme for ECG beat classification based on independent component analysis Expert Syst. Appl. 33 824-9
31. Yu S-N and Chen Y-H 2007 Electrocardiogram beat classification based on wavelet transformation and probabilistic neural network Pattern Recogn. Lett. 28 1142-50
32. Zhang H and Zhang L-Q 2005 ECG analysis based on PCA and support vector machines Int. Conf. Neural Networks and Brain, 2005. ICNN&B '05 (13-15 October 2005) vol 2 pp 743-7