Mechanomyography sensor development, related signal processing, and applications: A systematic review

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Main Authors: Md. Anamul, Islam, Sundaraj, Kenneth, Prof. Dr., R. Badlishah Ahmad, Prof. Dr., Nizam Uddin, Ahamed, Md. Asraf, Ali
Other Authors: anamulislam.phd@gmail.co
Format: Article
Language:English
Published: IEEE Conference Publications 2014
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Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33384
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spelling my.unimap-333842014-04-07T11:00:20Z Mechanomyography sensor development, related signal processing, and applications: A systematic review Md. Anamul, Islam Sundaraj, Kenneth, Prof. Dr. R. Badlishah Ahmad, Prof. Dr. Nizam Uddin, Ahamed Md. Asraf, Ali anamulislam.phd@gmail.co kenneth@unimap.edu.my badli@unimap.edu.my ahamed1557@hotmail.com asrafbabu@hotmail.com Mechanomyography Muscle characteristics assessment Prosthesis control Sensor development Signal processing Link to publisher's homepage at http://ieeexplore.ieee.org/ Mechanomyography (MMG) is extensively used in the research of sensor development, signal processing, characterization of muscle activity, development of prosthesis and/or switch control, diagnosis of neuromuscular disorders, and as a medical rehabilitation tool. Despite much existing MMG research, there has been no systematic review of these. This paper aims to determine the current status of MMG in sensor development, related signal processing, and applications. Six electronic databases were extensively searched for potentially eligible studies published between 2003 and 2012. From a total of 175 citations, 119 were selected for full-text evaluation and 86 potential studies were identified for further analysis. This systematic review initially reveals that the development of accelerometers for MMG is still in the initial stage. Another important finding of this paper is that sensor placement location on muscles may influence the MMG signal. In addition, we observe that the majority of research processes MMG signals using wavelet transform. Time/frequency domain analysis of MMG signals provides useful information to examine muscle. In addition, we find that MMG may be applied to diagnose muscle conditions, to control prosthesis and/or switch devices, to assess muscle activities during exercises, to study motor unit activity, and to identify the type of muscle fiber. Finally, we find that the majority of the studies use accelerometers as sensors for MMG measurements. We also observe that currently MMG-based rehabilitation is still in a nascent stage. In conclusion, we recommend further improvements of MMG in the areas of sensor development, particularly on accelerometers, and signal processing aspects, as well as increasing future applications of the technique in prosthesis and/or switch control, clinical practices, and rehabilitation. 2014-04-03T08:42:20Z 2014-04-03T08:42:20Z 2013 Article IEEE Sensors Journal, vol. 13(7), 2013, pages 2499-2516 1530-437X http://dspace.unimap.edu.my:80/dspace/handle/123456789/33384 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6490328&tag=1 http://dx.doi.org/10.1109/JSEN.2013.2255982 en IEEE Conference Publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Mechanomyography
Muscle characteristics assessment
Prosthesis control
Sensor development
Signal processing
spellingShingle Mechanomyography
Muscle characteristics assessment
Prosthesis control
Sensor development
Signal processing
Md. Anamul, Islam
Sundaraj, Kenneth, Prof. Dr.
R. Badlishah Ahmad, Prof. Dr.
Nizam Uddin, Ahamed
Md. Asraf, Ali
Mechanomyography sensor development, related signal processing, and applications: A systematic review
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 anamulislam.phd@gmail.co
author_facet anamulislam.phd@gmail.co
Md. Anamul, Islam
Sundaraj, Kenneth, Prof. Dr.
R. Badlishah Ahmad, Prof. Dr.
Nizam Uddin, Ahamed
Md. Asraf, Ali
format Article
author Md. Anamul, Islam
Sundaraj, Kenneth, Prof. Dr.
R. Badlishah Ahmad, Prof. Dr.
Nizam Uddin, Ahamed
Md. Asraf, Ali
author_sort Md. Anamul, Islam
title Mechanomyography sensor development, related signal processing, and applications: A systematic review
title_short Mechanomyography sensor development, related signal processing, and applications: A systematic review
title_full Mechanomyography sensor development, related signal processing, and applications: A systematic review
title_fullStr Mechanomyography sensor development, related signal processing, and applications: A systematic review
title_full_unstemmed Mechanomyography sensor development, related signal processing, and applications: A systematic review
title_sort mechanomyography sensor development, related signal processing, and applications: a systematic review
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33384
_version_ 1643797158583861248
score 13.214268