DocumentCode :
3775430
Title :
Design of movement sequences for arm rehabilitation of post-stroke
Author :
Rashidah Suhaimi;Kamil. S. Talha;Khairunizam Wan;Mohd Asri Ariffin
Author_Institution :
Advanced Intelligent Computing and Sustainability, Research Group, School of Mechatronic, Universiti Malaysia Perlis, Kampus Pauh Putra, 02600, Arau, MALAYSIA
fYear :
2015
Firstpage :
320
Lastpage :
324
Abstract :
This article presents the design of movement sequences for arm rehabilitation of stroke patient. The objective of this research is to develop the best movement sequences suitable for arm rehabilitation of hemiparesis sufferers based on the features analyzed that represent muscle activity. 8 healthy subjects including both male and female performed four arm movement sequences task consist of arm lifting and reaching movement in real environment. Muscle activities are recorded using electromyography (EMG) involving deltoid anterior, deltoid lateral, biceps and triceps. Based on the previous research, Amount of movement (AOM) feature is calculated to observe the muscle activation for each movement sequence task. The experimental results show that it is likely to produce optimum arm movement sequences for arm rehabilitation and the sequences are suitable to deploy in virtual reality in future research.
Keywords :
"Muscles","Electromyography","Conferences","Virtual reality","Training","Feature extraction","Control systems"
Publisher :
ieee
Conference_Titel :
Control System, Computing and Engineering (ICCSCE), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICCSCE.2015.7482205
Filename :
7482205
Link To Document :
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