Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people

The social demands for the Quality Of Life (QOL) are increasing with the exponentially expanding silver generation. To improve the QOL of the disabled and elderly people, robotic researchers and biomedical engineers have been trying to combine their techniques into the rehabilitation systems. Vario...

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Main Authors:	Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran
Format:	Article
Language:	English
Published:	Science Publications 2010
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/5616/ http://irep.iium.edu.my/5616/ http://irep.iium.edu.my/5616/1/Advances_in_Electromyogram_Signal_Classification_to_Improve_the_Quality_of_Life_for_the_Disabled_and_Aged_People.pdf

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spelling	iium-56162011-12-09T04:01:48Z http://irep.iium.edu.my/5616/ Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran T Technology (General) The social demands for the Quality Of Life (QOL) are increasing with the exponentially expanding silver generation. To improve the QOL of the disabled and elderly people, robotic researchers and biomedical engineers have been trying to combine their techniques into the rehabilitation systems. Various biomedical signals (biosignals) acquired from a specialized tissue, organ, or cell system like the nervous system are the driving force for the entire system. Examples of biosignals include Electro-Encephalogram (EEG), Electrooculogram (EOG), Electroneurogram (ENG) and (EMG). Approach: Among the biosignals, the research on EMG signal processing and controlling is currently expanding in various directions. EMG signal based research is ongoing for the development of simple, robust, user friendly, efficient interfacing devices/systems for the disabled. The advancement can be observed in the area of robotic devices, prosthesis limb, exoskeleton, wearable computer, I/O for virtual reality games and physical exercise equipments. An EMG signal based graphical controller or interfacing system enables the physically disabled to use word processing programs, other personal computer software and internet. Results: Depending on the application, the acquired and processed signals need to be classified for interpreting into mechanical force or machine/computer command. Conclusion: This study focused on the advances and improvements on different methodologies used for EMG signal classification with their efficiency, flexibility and applications. This review will be beneficial to the EMG signal researchers as a reference and comparison study of EMG classifier. For the development of robust, flexible and efficient applications,this study opened a pathway to the researchers in performing future comparative studies between different EMG classification methods. Science Publications 2010 Article PeerReviewed application/pdf en http://irep.iium.edu.my/5616/1/Advances_in_Electromyogram_Signal_Classification_to_Improve_the_Quality_of_Life_for_the_Disabled_and_Aged_People.pdf Ahsan, Md. Rezwanul and Ibrahimy, Muhammad Ibn and Khalifa, Othman Omran (2010) Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people. Journal of Computer Science, 6 (7). pp. 705-715. ISSN 1549-3636 http://thescipub.com/jcs.toc
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people
description	The social demands for the Quality Of Life (QOL) are increasing with the exponentially expanding silver generation. To improve the QOL of the disabled and elderly people, robotic researchers and biomedical engineers have been trying to combine their techniques into the rehabilitation systems. Various biomedical signals (biosignals) acquired from a specialized tissue, organ, or cell system like the nervous system are the driving force for the entire system. Examples of biosignals include Electro-Encephalogram (EEG), Electrooculogram (EOG), Electroneurogram (ENG) and (EMG). Approach: Among the biosignals, the research on EMG signal processing and controlling is currently expanding in various directions. EMG signal based research is ongoing for the development of simple, robust, user friendly, efficient interfacing devices/systems for the disabled. The advancement can be observed in the area of robotic devices, prosthesis limb, exoskeleton, wearable computer, I/O for virtual reality games and physical exercise equipments. An EMG signal based graphical controller or interfacing system enables the physically disabled to use word processing programs, other personal computer software and internet. Results: Depending on the application, the acquired and processed signals need to be classified for interpreting into mechanical force or machine/computer command. Conclusion: This study focused on the advances and improvements on different methodologies used for EMG signal classification with their efficiency, flexibility and applications. This review will be beneficial to the EMG signal researchers as a reference and comparison study of EMG classifier. For the development of robust, flexible and efficient applications,this study opened a pathway to the researchers in performing future comparative studies between different EMG classification methods.
format	Article
author	Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran
author_facet	Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran
author_sort	Ahsan, Md. Rezwanul
title	Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people
title_short	Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people
title_full	Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people
title_fullStr	Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people
title_full_unstemmed	Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people
title_sort	advances in electromyogram signal classification to improve the quality of life for the disabled and aged people
publisher	Science Publications
publishDate	2010
url	http://irep.iium.edu.my/5616/ http://irep.iium.edu.my/5616/ http://irep.iium.edu.my/5616/1/Advances_in_Electromyogram_Signal_Classification_to_Improve_the_Quality_of_Life_for_the_Disabled_and_Aged_People.pdf
first_indexed	2023-09-18T20:14:18Z
last_indexed	2023-09-18T20:14:18Z
_version_	1777407684447830016

Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people

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