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Neural Computing and Applications

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01.04.2006 | Original Article

Application of independent component analysis in removing artefacts from the electrocardiogram

verfasst von: Taigang He, Gari Clifford, Lionel Tarassenko

Erschienen in: Neural Computing and Applications | Ausgabe 2/2006

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Abstract

Routinely recorded electrocardiograms (ECGs) are often corrupted by different types of artefacts and many efforts have been made to enhance their quality by reducing the noise or artefacts. This paper addresses the problem of removing noise and artefacts from ECGs using independent component analysis (ICA). An ICA algorithm is tested on three-channel ECG recordings taken from human subjects, mostly in the coronary care unit. Results are presented that show that ICA can detect and remove a variety of noise and artefact sources in these ECGs. One difficulty with the application of ICA is the determination of the order of the independent components. A new technique based on simple statistical parameters is proposed to solve this problem in this application. The developed technique is successfully applied to the ECG data and offers potential for online processing of ECG using ICA.

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Paul JS, Reddy MR, Kumar VJ (2000) A transform domain SVD filter for suppression of muscle noise artefacts in exercise ECG’s. IEEE Trans Biomed Eng 3:654–663CrossRef

Talmon TL, Kors JA, Von JH (1986) Adaptive Gaussian filtering in routine ECG/VCG analysis. IEEE Trans Acoust Speech Signal Process ASSP-34:527–534CrossRef

Thakor NV, Zhu VS (1991) Application of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection. IEEE Trans Biomed Eng 38:785–793CrossRef

Bensadoun Y, Novakov E, Raoof K (1995) Multidimensional adaptive method for canceling EMG signals from the ECG signal. In: Roberge FA, Kearney RE (eds) 17th IEEE Ann Int Conf on Engng in Med and Biol Soc. Montreal, pp 299–300

Barros AK, Ohnishi N (1997) MSE behavior of biomedical event-related filters. IEEE Trans Biomed Eng 44:848–855CrossRef

Laguna P, Janè R, Meste O et’al (1992) Adaptive filter for event-related bioelectric signals using an impulse correlated reference input: comparison with signal averaging techniques. IEEE Trans Biomed Eng 39:1032–1043CrossRef

Vaz C, Kong X, Thakor NV (1994) An adaptive estimation of periodic signals using a Fourier linear combiner. IEEE Trans Signal Process 42:1–10CrossRef

Kanjilal PP, Palit S (1995) On multiple pattern extraction using singular value decomposition. IEEE Trans Signal Process 43:1536–1540CrossRef

Wisbeck JO, Garcia RO (1998) Application of neural networks to separate interferences and ECG signals. In: Proceedings of IEEE international Caracas conference on devices, circuits and systems, pp 291–294

10.

Speirs CA, Soraghan JJ, Stewart RW et’al (1994) Ventricular late potential detection from bispectral analysis of ST-segments. In: Proceedings of EUSIPCO–94, September 1994, pp 1129–1132

11.

Jung T-P, Makeig S, Lee T-W et’al (2000) The 2nd international workshop on independent component analysis and signal separation, pp 633–644

12.

Cardoso JF (1998) Multidimensional independent component analysis. In: Proceedings of ICASSP ’98, Seattle, pp 1941–1944

13.

Wisbeck JO, Barros AK, Ojeda R (1998) Application of ICA in the separation of breathing artefacts in ECG signals. International conference on neural information processing, (ICONIP’98), Kyushu, Japan

14.

Barros AK, Mansour A, Ohnishi N (1998) Removing artefacts from electrocardiographic signals using independent component analysis. Neurocomputing 22:173–186MATHCrossRef

15.

Tong S, Bezerianos A, Paul J et’al (2001) Removal of ECG interference from the EEG recordings in small animals using independent component analysis. J Neurosci Meth 108:11–17CrossRef

16.

Jung TP, Makeig S, Humphries C et’al (2000) Removing electroencephalographic artefacts by blind source separation. Psychophysiology 37:163–178CrossRef

17.

Hyvarinen A (1999) Survey on independent component analysis. Neural Comput Survey 2:94–128

18.

Cardoso JF (1999) High-order contrasts for independent component analysis. Neural Comput 11:157–192CrossRef

19.

Huber PJ (1985) Projection pursuit. Ann Stat 13(2):435–475MATHCrossRefMathSciNet

20.

Tarassenko L, Townsend N, Clifford G et’al (2001) Medical signal processing using the software monitor. In: Proceedings of IEE/DERA workshop on intelligent signal processing, Birmingham, February, pp 3/1–3/4

21.

Anderson ST, Downs WG, Lander P et’al (1995) Advanced electrocardiography. Spacelabs medical biophysical measurement, SpaceLabs Medical Inc., Washington

22.

ANSI/AAMI EC38–1994, Ambulatory electrocardiographs. American National Standard, August 1994

23.

McClellan P (1979) Algorithm 5.1. Programs for digital signal processing. IEEE Press, Wiley, New York

24.

Clifford G (1999) The software monitor project—novelty detection and classification in electrocardiograms. DPhil transfer report, Department of Engineering Science, University of Oxford

25.

Houghton A, Gray D (1997) Making sense of the ECG. Oxford University Press, Oxford

Titel: Application of independent component analysis in removing artefacts from the electrocardiogram
verfasst von: Taigang He
Gari Clifford
Lionel Tarassenko
Publikationsdatum: 01.04.2006
Verlag: Springer-Verlag
Erschienen in: Neural Computing and Applications / Ausgabe 2/2006
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-005-0013-y

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