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Motion artefact removals for wearable ECG using stationary wavelet transform
Wearable Electrocardiogram (ECG) is attracting much attention in daily healthcare applications. From the viewpoint of long-term use, it is desired that the electrodes are non-contact with the human body. In this study, the authors propose an algorithm using the stationary wavelet transform (SWT) to...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Institution of Engineering and Technology
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5569871/ https://www.ncbi.nlm.nih.gov/pubmed/28868151 http://dx.doi.org/10.1049/htl.2016.0100 |
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author | Nagai, Shuto Anzai, Daisuke Wang, Jianqing |
author_facet | Nagai, Shuto Anzai, Daisuke Wang, Jianqing |
author_sort | Nagai, Shuto |
collection | PubMed |
description | Wearable Electrocardiogram (ECG) is attracting much attention in daily healthcare applications. From the viewpoint of long-term use, it is desired that the electrodes are non-contact with the human body. In this study, the authors propose an algorithm using the stationary wavelet transform (SWT) to remove motion artefact superimposed on ECG signal when using non-contact capacitively coupling electrodes. The authors evaluate the effect on motion artefact removal of this algorithm by applying it to various ECG signals with motion artefacts superimposed. As a result, the correlation coefficients of ECG signals with respect to the clean ones have been improved from 0.71 to 0.88 on median before and after motion artefact removal, which demonstrates the validity of the proposed SWT-based algorithm. |
format | Online Article Text |
id | pubmed-5569871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Institution of Engineering and Technology |
record_format | MEDLINE/PubMed |
spelling | pubmed-55698712017-09-01 Motion artefact removals for wearable ECG using stationary wavelet transform Nagai, Shuto Anzai, Daisuke Wang, Jianqing Healthc Technol Lett Article Wearable Electrocardiogram (ECG) is attracting much attention in daily healthcare applications. From the viewpoint of long-term use, it is desired that the electrodes are non-contact with the human body. In this study, the authors propose an algorithm using the stationary wavelet transform (SWT) to remove motion artefact superimposed on ECG signal when using non-contact capacitively coupling electrodes. The authors evaluate the effect on motion artefact removal of this algorithm by applying it to various ECG signals with motion artefacts superimposed. As a result, the correlation coefficients of ECG signals with respect to the clean ones have been improved from 0.71 to 0.88 on median before and after motion artefact removal, which demonstrates the validity of the proposed SWT-based algorithm. The Institution of Engineering and Technology 2017-06-14 /pmc/articles/PMC5569871/ /pubmed/28868151 http://dx.doi.org/10.1049/htl.2016.0100 Text en http://creativecommons.org/licenses/by/3.0/ This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
spellingShingle | Article Nagai, Shuto Anzai, Daisuke Wang, Jianqing Motion artefact removals for wearable ECG using stationary wavelet transform |
title | Motion artefact removals for wearable ECG using stationary wavelet transform |
title_full | Motion artefact removals for wearable ECG using stationary wavelet transform |
title_fullStr | Motion artefact removals for wearable ECG using stationary wavelet transform |
title_full_unstemmed | Motion artefact removals for wearable ECG using stationary wavelet transform |
title_short | Motion artefact removals for wearable ECG using stationary wavelet transform |
title_sort | motion artefact removals for wearable ecg using stationary wavelet transform |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5569871/ https://www.ncbi.nlm.nih.gov/pubmed/28868151 http://dx.doi.org/10.1049/htl.2016.0100 |
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