Neuromotor Rehabilitation System with Real-Time Biofeedback

Aung, Y; Al-Jumaily, A

Neuromotor Rehabilitation System with Real-Time Biofeedback

Aung, Y Al-Jumaily, A

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Publisher:: MIR Labs
Publication Type:: Journal Article
Citation:: International Journal of Computer Information Systems and Industrial Management (IJCISIM), 2013, 5 pp. 550 - 556
Issue Date:: 2013-01

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Field	Value	Language
dc.contributor.author	Aung, Y	en_US
dc.contributor.author	Al-Jumaily, A https://orcid.org/0000-0003-0297-2463	en_US
dc.date.issued	2013-01	en_US
dc.identifier.citation	International Journal of Computer Information Systems and Industrial Management (IJCISIM), 2013, 5 pp. 550 - 556	en_US
dc.identifier.issn	2150-7988	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26658
dc.description.abstract	Physical disabilities which caused by neuromotor impairment due to Traumatic Brain Injury (TBI), Spinal Cord Injury (SCI) and Cerebrovascular Accident (CVA) affect the persons quality of life. Therefore, physical rehabilitations are required to be performed for the restoration of lost functions as a core treatment for such disabilities. However, the physical rehabilitations are too labor-intensive due to the nature of one-to-one attention in healthcare sectors. Moreover, this kind of injuries and accident cost over $10 billion per annum in healthcare sectors. To overcome above mentioned problems, this paper presents the development of intelligent biofeedback neuromotor rehabilitation system with low cost and motivational approach to close the gap in shortage of therapists, high healthcare cost of TBI, SCI and CVA. Our system designed for user motivation to perform the exercise longer and be used with minimum therapist supervision at home. The rehabilitation exercise aims to increase the upper limb range of motion, and strengthen the associate muscles. Our system utilized sEMG signals as a biofeedback. The users sEMG signals will attain and detect the therapist defined sEMG threshold level to display active muscle in real time during performing exercises. While the system works to retrain the elastic brain via fast recovery method, it will close the gap for the required information, by therapists, about monitoring and tracks the users muscle performance. The effectiveness of the proposed system has been evaluated by performing usability test.	en_US
dc.publisher	MIR Labs	en_US
dc.relation.ispartof	International Journal of Computer Information Systems and Industrial Management (IJCISIM)	en_US
dc.title	Neuromotor Rehabilitation System with Real-Time Biofeedback	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.for	090305 Rehabilitation Engineering	en_US
utslib.for	080111 Virtual Reality and Related Simulation	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.volume	5	en_US

Abstract:

Physical disabilities which caused by neuromotor impairment due to Traumatic Brain Injury (TBI), Spinal Cord Injury (SCI) and Cerebrovascular Accident (CVA) affect the persons quality of life. Therefore, physical rehabilitations are required to be performed for the restoration of lost functions as a core treatment for such disabilities. However, the physical rehabilitations are too labor-intensive due to the nature of one-to-one attention in healthcare sectors. Moreover, this kind of injuries and accident cost over $10 billion per annum in healthcare sectors. To overcome above mentioned problems, this paper presents the development of intelligent biofeedback neuromotor rehabilitation system with low cost and motivational approach to close the gap in shortage of therapists, high healthcare cost of TBI, SCI and CVA. Our system designed for user motivation to perform the exercise longer and be used with minimum therapist supervision at home. The rehabilitation exercise aims to increase the upper limb range of motion, and strengthen the associate muscles. Our system utilized sEMG signals as a biofeedback. The users sEMG signals will attain and detect the therapist defined sEMG threshold level to display active muscle in real time during performing exercises. While the system works to retrain the elastic brain via fast recovery method, it will close the gap for the required information, by therapists, about monitoring and tracks the users muscle performance. The effectiveness of the proposed system has been evaluated by performing usability test.

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http://hdl.handle.net/10453/26658