In recorded bioelectric signals, such as the electrocardiogram, sinusoidal interference from power lines or other sources causes distortion in the signal and may lead to misdiagnosis. For long or continuous recordings, adaptive filtering can be effective in minimizing the interference. For short recording, the options are limited. Subtractive methods have been used, but they do not distinguish between the interference and signal components with similar frequency. A new method can distinguish between signal and interference, so that the interference can be removed with very small residual error. In clinical recordings, the frequency of powerline interference is known, but the adaptive nature of the algorithm allows extension to cases when the frequency of interference is not known exactly.
Published in | International Journal of Biomedical Science and Engineering (Volume 2, Issue 4) |
DOI | 10.11648/j.ijbse.20140204.11 |
Page(s) | 27-32 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2014. Published by Science Publishing Group |
Interference Removal, Electrocardiogram, Time-Frequency, Filtering
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APA Style
Brandon S. Coventry, Cecil W. Thomas. (2014). Time-Frequency Equivalence in Removing Sinusoidal Interference from Electrocardiograms. International Journal of Biomedical Science and Engineering, 2(4), 27-32. https://doi.org/10.11648/j.ijbse.20140204.11
ACS Style
Brandon S. Coventry; Cecil W. Thomas. Time-Frequency Equivalence in Removing Sinusoidal Interference from Electrocardiograms. Int. J. Biomed. Sci. Eng. 2014, 2(4), 27-32. doi: 10.11648/j.ijbse.20140204.11
AMA Style
Brandon S. Coventry, Cecil W. Thomas. Time-Frequency Equivalence in Removing Sinusoidal Interference from Electrocardiograms. Int J Biomed Sci Eng. 2014;2(4):27-32. doi: 10.11648/j.ijbse.20140204.11
@article{10.11648/j.ijbse.20140204.11, author = {Brandon S. Coventry and Cecil W. Thomas}, title = {Time-Frequency Equivalence in Removing Sinusoidal Interference from Electrocardiograms}, journal = {International Journal of Biomedical Science and Engineering}, volume = {2}, number = {4}, pages = {27-32}, doi = {10.11648/j.ijbse.20140204.11}, url = {https://doi.org/10.11648/j.ijbse.20140204.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijbse.20140204.11}, abstract = {In recorded bioelectric signals, such as the electrocardiogram, sinusoidal interference from power lines or other sources causes distortion in the signal and may lead to misdiagnosis. For long or continuous recordings, adaptive filtering can be effective in minimizing the interference. For short recording, the options are limited. Subtractive methods have been used, but they do not distinguish between the interference and signal components with similar frequency. A new method can distinguish between signal and interference, so that the interference can be removed with very small residual error. In clinical recordings, the frequency of powerline interference is known, but the adaptive nature of the algorithm allows extension to cases when the frequency of interference is not known exactly.}, year = {2014} }
TY - JOUR T1 - Time-Frequency Equivalence in Removing Sinusoidal Interference from Electrocardiograms AU - Brandon S. Coventry AU - Cecil W. Thomas Y1 - 2014/09/20 PY - 2014 N1 - https://doi.org/10.11648/j.ijbse.20140204.11 DO - 10.11648/j.ijbse.20140204.11 T2 - International Journal of Biomedical Science and Engineering JF - International Journal of Biomedical Science and Engineering JO - International Journal of Biomedical Science and Engineering SP - 27 EP - 32 PB - Science Publishing Group SN - 2376-7235 UR - https://doi.org/10.11648/j.ijbse.20140204.11 AB - In recorded bioelectric signals, such as the electrocardiogram, sinusoidal interference from power lines or other sources causes distortion in the signal and may lead to misdiagnosis. For long or continuous recordings, adaptive filtering can be effective in minimizing the interference. For short recording, the options are limited. Subtractive methods have been used, but they do not distinguish between the interference and signal components with similar frequency. A new method can distinguish between signal and interference, so that the interference can be removed with very small residual error. In clinical recordings, the frequency of powerline interference is known, but the adaptive nature of the algorithm allows extension to cases when the frequency of interference is not known exactly. VL - 2 IS - 4 ER -