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EMG Processing Based Measures of Fatigue Assessment during Manual Lifting
Manual lifting is one of the common practices used in the industries to transport or move objects to a desired place. Nowadays, even though mechanized equipment is widely available, manual lifting is still considered as an essential way to perform material handling task. Improper lifting strategies...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337807/ https://www.ncbi.nlm.nih.gov/pubmed/28303251 http://dx.doi.org/10.1155/2017/3937254 |
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author | Shair, E. F. Ahmad, S. A. Marhaban, M. H. Mohd Tamrin, S. B. Abdullah, A. R. |
author_facet | Shair, E. F. Ahmad, S. A. Marhaban, M. H. Mohd Tamrin, S. B. Abdullah, A. R. |
author_sort | Shair, E. F. |
collection | PubMed |
description | Manual lifting is one of the common practices used in the industries to transport or move objects to a desired place. Nowadays, even though mechanized equipment is widely available, manual lifting is still considered as an essential way to perform material handling task. Improper lifting strategies may contribute to musculoskeletal disorders (MSDs), where overexertion contributes as the highest factor. To overcome this problem, electromyography (EMG) signal is used to monitor the workers' muscle condition and to find maximum lifting load, lifting height and number of repetitions that the workers are able to handle before experiencing fatigue to avoid overexertion. Past researchers have introduced several EMG processing techniques and different EMG features that represent fatigue indices in time, frequency, and time-frequency domain. The impact of EMG processing based measures in fatigue assessment during manual lifting are reviewed in this paper. It is believed that this paper will greatly benefit researchers who need a bird's eye view of the biosignal processing which are currently available, thus determining the best possible techniques for lifting applications. |
format | Online Article Text |
id | pubmed-5337807 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-53378072017-03-16 EMG Processing Based Measures of Fatigue Assessment during Manual Lifting Shair, E. F. Ahmad, S. A. Marhaban, M. H. Mohd Tamrin, S. B. Abdullah, A. R. Biomed Res Int Review Article Manual lifting is one of the common practices used in the industries to transport or move objects to a desired place. Nowadays, even though mechanized equipment is widely available, manual lifting is still considered as an essential way to perform material handling task. Improper lifting strategies may contribute to musculoskeletal disorders (MSDs), where overexertion contributes as the highest factor. To overcome this problem, electromyography (EMG) signal is used to monitor the workers' muscle condition and to find maximum lifting load, lifting height and number of repetitions that the workers are able to handle before experiencing fatigue to avoid overexertion. Past researchers have introduced several EMG processing techniques and different EMG features that represent fatigue indices in time, frequency, and time-frequency domain. The impact of EMG processing based measures in fatigue assessment during manual lifting are reviewed in this paper. It is believed that this paper will greatly benefit researchers who need a bird's eye view of the biosignal processing which are currently available, thus determining the best possible techniques for lifting applications. Hindawi Publishing Corporation 2017 2017-02-19 /pmc/articles/PMC5337807/ /pubmed/28303251 http://dx.doi.org/10.1155/2017/3937254 Text en Copyright © 2017 E. F. Shair et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Shair, E. F. Ahmad, S. A. Marhaban, M. H. Mohd Tamrin, S. B. Abdullah, A. R. EMG Processing Based Measures of Fatigue Assessment during Manual Lifting |
title | EMG Processing Based Measures of Fatigue Assessment during Manual Lifting |
title_full | EMG Processing Based Measures of Fatigue Assessment during Manual Lifting |
title_fullStr | EMG Processing Based Measures of Fatigue Assessment during Manual Lifting |
title_full_unstemmed | EMG Processing Based Measures of Fatigue Assessment during Manual Lifting |
title_short | EMG Processing Based Measures of Fatigue Assessment during Manual Lifting |
title_sort | emg processing based measures of fatigue assessment during manual lifting |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337807/ https://www.ncbi.nlm.nih.gov/pubmed/28303251 http://dx.doi.org/10.1155/2017/3937254 |
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