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Bae, Joonbum
Bio-robotics and Control Lab.
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A gait rehabilitation strategy inspired by an iterative learning algorithm

Author(s)
Bae, JoonbumTomizuka, Masayoshi
Issued Date
2012-03
DOI
10.1016/j.mechatronics.2012.01.009
URI
https://scholarworks.unist.ac.kr/handle/201301/3001
Fulltext
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84858155931
Citation
MECHATRONICS, v.22, no.2, pp.213 - 221
Abstract
Robotic gait rehabilitation devices enable efficient and convenient gait rehabilitation by mimicking the functions of physical therapists. In manual gait rehabilitation training, physical therapists have patients practice and memorize normal gait patterns by applying assistive torque to the patient's joint once the patient's gait deviates from the normal gait. Thus, one of the most important factors in robotic gait rehabilitation devices is to determine the assistive torque to the patient's joint during rehabilitation training. In this paper, the gait rehabilitation strategy inspired by an iterative learning algorithm is proposed, which uses the repetitive characteristic of gait motions. In the proposed strategy, the assistive joint torque in the current stride is calculated based on the information from previous strides. Simulation results and experimental results using an active knee orthosis are presented, which verify that the proposed strategy can be used to calculate appropriate assistive joint torque to excise the desired motions for rehabilitation.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
ISSN
0957-4158
Keyword (Author)
Gait rehabilitation strategyIterative learning algorithmRobotic gait rehabilitation device
Keyword
SERIES ELASTIC ACTUATORROBOTIC ORTHOSISDESIGNSYSTEMMACHINEWALKING

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