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Bae, Joonbum
Bio-Robotics and Control (BiRC) Lab
Research Interests
  • Design and control of physical human-robot interaction systems

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A gait rehabilitation strategy inspired by an iterative learning algorithm

Cited 3 times inthomson ciCited 5 times inthomson ci
Title
A gait rehabilitation strategy inspired by an iterative learning algorithm
Author
Bae, JoonbumTomizuka, Masayoshi
Keywords
Assistive; Gait motions; Gait pattern; Gait rehabilitation; Iterative learning; Iterative learning algorithm; Joint torques; Orthosis; Rehabilitation training; Robotic gait rehabilitation; Robotic gait rehabilitation device
Issue Date
201203
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
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.
URI
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DOI
http://dx.doi.org/10.1016/j.mechatronics.2012.01.009
ISSN
0957-4158
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