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Comparison of six electromyography acquisition setups on hand movement classification tasks
Hand prostheses controlled by surface electromyography are promising due to the non-invasive approach and the control capabilities offered by machine learning. Nevertheless, dexterous prostheses are still scarcely spread due to control difficulties, low robustness and often prohibitive costs. Severa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638457/ https://www.ncbi.nlm.nih.gov/pubmed/29023548 http://dx.doi.org/10.1371/journal.pone.0186132 |
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author | Pizzolato, Stefano Tagliapietra, Luca Cognolato, Matteo Reggiani, Monica Müller, Henning Atzori, Manfredo |
author_facet | Pizzolato, Stefano Tagliapietra, Luca Cognolato, Matteo Reggiani, Monica Müller, Henning Atzori, Manfredo |
author_sort | Pizzolato, Stefano |
collection | PubMed |
description | Hand prostheses controlled by surface electromyography are promising due to the non-invasive approach and the control capabilities offered by machine learning. Nevertheless, dexterous prostheses are still scarcely spread due to control difficulties, low robustness and often prohibitive costs. Several sEMG acquisition setups are now available, ranging in terms of costs between a few hundred and several thousand dollars. The objective of this paper is the relative comparison of six acquisition setups on an identical hand movement classification task, in order to help the researchers to choose the proper acquisition setup for their requirements. The acquisition setups are based on four different sEMG electrodes (including Otto Bock, Delsys Trigno, Cometa Wave + Dormo ECG and two Thalmic Myo armbands) and they were used to record more than 50 hand movements from intact subjects with a standardized acquisition protocol. The relative performance of the six sEMG acquisition setups is compared on 41 identical hand movements with a standardized feature extraction and data analysis pipeline aimed at performing hand movement classification. Comparable classification results are obtained with three acquisition setups including the Delsys Trigno, the Cometa Wave and the affordable setup composed of two Myo armbands. The results suggest that practical sEMG tests can be performed even when costs are relevant (e.g. in small laboratories, developing countries or use by children). All the presented datasets can be used for offline tests and their quality can easily be compared as the data sets are publicly available. |
format | Online Article Text |
id | pubmed-5638457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56384572017-10-20 Comparison of six electromyography acquisition setups on hand movement classification tasks Pizzolato, Stefano Tagliapietra, Luca Cognolato, Matteo Reggiani, Monica Müller, Henning Atzori, Manfredo PLoS One Research Article Hand prostheses controlled by surface electromyography are promising due to the non-invasive approach and the control capabilities offered by machine learning. Nevertheless, dexterous prostheses are still scarcely spread due to control difficulties, low robustness and often prohibitive costs. Several sEMG acquisition setups are now available, ranging in terms of costs between a few hundred and several thousand dollars. The objective of this paper is the relative comparison of six acquisition setups on an identical hand movement classification task, in order to help the researchers to choose the proper acquisition setup for their requirements. The acquisition setups are based on four different sEMG electrodes (including Otto Bock, Delsys Trigno, Cometa Wave + Dormo ECG and two Thalmic Myo armbands) and they were used to record more than 50 hand movements from intact subjects with a standardized acquisition protocol. The relative performance of the six sEMG acquisition setups is compared on 41 identical hand movements with a standardized feature extraction and data analysis pipeline aimed at performing hand movement classification. Comparable classification results are obtained with three acquisition setups including the Delsys Trigno, the Cometa Wave and the affordable setup composed of two Myo armbands. The results suggest that practical sEMG tests can be performed even when costs are relevant (e.g. in small laboratories, developing countries or use by children). All the presented datasets can be used for offline tests and their quality can easily be compared as the data sets are publicly available. Public Library of Science 2017-10-12 /pmc/articles/PMC5638457/ /pubmed/29023548 http://dx.doi.org/10.1371/journal.pone.0186132 Text en © 2017 Pizzolato et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Pizzolato, Stefano Tagliapietra, Luca Cognolato, Matteo Reggiani, Monica Müller, Henning Atzori, Manfredo Comparison of six electromyography acquisition setups on hand movement classification tasks |
title | Comparison of six electromyography acquisition setups on hand movement classification tasks |
title_full | Comparison of six electromyography acquisition setups on hand movement classification tasks |
title_fullStr | Comparison of six electromyography acquisition setups on hand movement classification tasks |
title_full_unstemmed | Comparison of six electromyography acquisition setups on hand movement classification tasks |
title_short | Comparison of six electromyography acquisition setups on hand movement classification tasks |
title_sort | comparison of six electromyography acquisition setups on hand movement classification tasks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638457/ https://www.ncbi.nlm.nih.gov/pubmed/29023548 http://dx.doi.org/10.1371/journal.pone.0186132 |
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