Wavelet-based performance in denoising ECG signal
Electrocardiogram (ECG) is a powerful tool which allows for diagnosing heart condition. Nowadays, wearable ECG recording devices are used in continuous monitoring and to provide health related information. However, these systems suffer from motion artifacts which remains an unsolved problem. In this...
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Association for Computing Machinery
2016
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my.utm.729602017-11-29T23:58:38Z http://eprints.utm.my/id/eprint/72960/ Wavelet-based performance in denoising ECG signal Hadji, S. E. Salleh, M. Rohani, M. F. Kamat, M. QA75 Electronic computers. Computer science Electrocardiogram (ECG) is a powerful tool which allows for diagnosing heart condition. Nowadays, wearable ECG recording devices are used in continuous monitoring and to provide health related information. However, these systems suffer from motion artifacts which remains an unsolved problem. In this paper, two wavelet-based techniques are presented and applied for ECG denoising with an evaluation of their performances. These methods are: wavelet shrinkage denoisingand multi-resolution thresholding using stationary wavelet transformation (SWT).An improved multi-resolution thresholding technique is proposed. This technique combines between the two former methods. Benchmark datasets and simulated noises were used to evaluate thedenoising techniques. The results shows that the current methods still cannot cope with motions artifacts, even the proposed technique improves only the smoothness of the ECG signal. Association for Computing Machinery 2016 Conference or Workshop Item PeerReviewed Hadji, S. E. and Salleh, M. and Rohani, M. F. and Kamat, M. (2016) Wavelet-based performance in denoising ECG signal. In: 8th International Conference on Signal Processing Systems, ICSPS 2016, 21 November 2016 through 24 November 2016, New Zealand. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014810675&doi=10.1145%2f3015166.3015212&partnerID=40&md5=9b42d7aebf050bdfa1180c1d162cb9ba |
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QA75 Electronic computers. Computer science Hadji, S. E. Salleh, M. Rohani, M. F. Kamat, M. Wavelet-based performance in denoising ECG signal |
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Electrocardiogram (ECG) is a powerful tool which allows for diagnosing heart condition. Nowadays, wearable ECG recording devices are used in continuous monitoring and to provide health related information. However, these systems suffer from motion artifacts which remains an unsolved problem. In this paper, two wavelet-based techniques are presented and applied for ECG denoising with an evaluation of their performances. These methods are: wavelet shrinkage denoisingand multi-resolution thresholding using stationary wavelet transformation (SWT).An improved multi-resolution thresholding technique is proposed. This technique combines between the two former methods. Benchmark datasets and simulated noises were used to evaluate thedenoising techniques. The results shows that the current methods still cannot cope with motions artifacts, even the proposed technique improves only the smoothness of the ECG signal. |
format |
Conference or Workshop Item |
author |
Hadji, S. E. Salleh, M. Rohani, M. F. Kamat, M. |
author_facet |
Hadji, S. E. Salleh, M. Rohani, M. F. Kamat, M. |
author_sort |
Hadji, S. E. |
title |
Wavelet-based performance in denoising ECG signal |
title_short |
Wavelet-based performance in denoising ECG signal |
title_full |
Wavelet-based performance in denoising ECG signal |
title_fullStr |
Wavelet-based performance in denoising ECG signal |
title_full_unstemmed |
Wavelet-based performance in denoising ECG signal |
title_sort |
wavelet-based performance in denoising ecg signal |
publisher |
Association for Computing Machinery |
publishDate |
2016 |
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http://eprints.utm.my/id/eprint/72960/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014810675&doi=10.1145%2f3015166.3015212&partnerID=40&md5=9b42d7aebf050bdfa1180c1d162cb9ba |
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1643656537194889216 |
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13.15806 |