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A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings
Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Alth...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6061514/ https://www.ncbi.nlm.nih.gov/pubmed/29327334 http://dx.doi.org/10.1007/s11517-017-1773-0 |
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author | Corera, Íñigo Eciolaza, Adrián Rubio, Oliver Malanda, Armando Rodríguez-Falces, Javier Navallas, Javier |
author_facet | Corera, Íñigo Eciolaza, Adrián Rubio, Oliver Malanda, Armando Rodríguez-Falces, Javier Navallas, Javier |
author_sort | Corera, Íñigo |
collection | PubMed |
description | Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Although the traditional processing based on the median filtering is effective in removing such interference, it distorts the physiological waveform of the scanning-EMG signal. In this study, we describe a new scanning-EMG signal processing algorithm that preserves the physiological signal waveform while effectively removing interference from other motor units. To obtain a cleaned-up version of the scanning signal, the masked least-squares smoothing (MLSS) algorithm recalculates and replaces each sample value of the signal using a least-squares smoothing in the spatial dimension, taking into account the information of only those samples that are not contaminated with activity of other motor units. The performance of the new algorithm with simulated scanning-EMG signals is studied and compared with the performance of the median algorithm and tested with real scanning signals. Results show that the MLSS algorithm distorts the waveform of the scanning-EMG signal much less than the median algorithm (approximately 3.5 dB gain), being at the same time very effective at removing interference components. [Figure: see text] |
format | Online Article Text |
id | pubmed-6061514 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-60615142018-08-09 A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings Corera, Íñigo Eciolaza, Adrián Rubio, Oliver Malanda, Armando Rodríguez-Falces, Javier Navallas, Javier Med Biol Eng Comput Original Article Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Although the traditional processing based on the median filtering is effective in removing such interference, it distorts the physiological waveform of the scanning-EMG signal. In this study, we describe a new scanning-EMG signal processing algorithm that preserves the physiological signal waveform while effectively removing interference from other motor units. To obtain a cleaned-up version of the scanning signal, the masked least-squares smoothing (MLSS) algorithm recalculates and replaces each sample value of the signal using a least-squares smoothing in the spatial dimension, taking into account the information of only those samples that are not contaminated with activity of other motor units. The performance of the new algorithm with simulated scanning-EMG signals is studied and compared with the performance of the median algorithm and tested with real scanning signals. Results show that the MLSS algorithm distorts the waveform of the scanning-EMG signal much less than the median algorithm (approximately 3.5 dB gain), being at the same time very effective at removing interference components. [Figure: see text] Springer Berlin Heidelberg 2018-01-11 2018 /pmc/articles/PMC6061514/ /pubmed/29327334 http://dx.doi.org/10.1007/s11517-017-1773-0 Text en © The Author(s) 2018 Open AccessThis article is 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, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Corera, Íñigo Eciolaza, Adrián Rubio, Oliver Malanda, Armando Rodríguez-Falces, Javier Navallas, Javier A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings |
title | A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings |
title_full | A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings |
title_fullStr | A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings |
title_full_unstemmed | A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings |
title_short | A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings |
title_sort | masked least-squares smoothing procedure for artifact reduction in scanning-emg recordings |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6061514/ https://www.ncbi.nlm.nih.gov/pubmed/29327334 http://dx.doi.org/10.1007/s11517-017-1773-0 |
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