Literature DB >> 23193241

Adaptive impedance control of a robotic orthosis for gait rehabilitation.

Shahid Hussain1, Sheng Q Xie, Prashant K Jamwal.   

Abstract

Intervention of robotic devices in the field of physical gait therapy can help in providing repetitive, systematic, and economically viable training sessions. Interactive or assist-as-needed (AAN) gait training encourages patient voluntary participation in the robotic gait training process which may aid in rapid motor function recovery. In this paper, a lightweight robotic gait training orthosis with two actuated and four passive degrees of freedom (DOFs) is proposed. The actuated DOFs were powered by pneumatic muscle actuators. An AAN gait training paradigm based on adaptive impedance control was developed to provide interactive robotic gait training. The proposed adaptive impedance control scheme adapts the robotic assistance according to the disability level and voluntary participation of human subjects. The robotic orthosis was operated in two gait training modes, namely, inactive mode and active mode, to evaluate the performance of the proposed control scheme. The adaptive impedance control scheme was evaluated on ten neurologically intact subjects. The experimental results demonstrate that an increase in voluntary participation of human subjects resulted in a decrease of the robotic assistance and vice versa. Further clinical evaluations with neurologically impaired subjects are required to establish the therapeutic efficacy of the adaptive-impedance-control-based AAN gait training strategy.

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Year:  2012        PMID: 23193241     DOI: 10.1109/TSMCB.2012.2222374

Source DB:  PubMed          Journal:  IEEE Trans Cybern        ISSN: 2168-2267            Impact factor:   11.448


  14 in total

1.  Knee Impedance Modulation to Control an Active Orthosis Using Insole Sensors.

Authors:  Ana Cecilia Villa-Parra; Denis Delisle-Rodriguez; Jessica Souza Lima; Anselmo Frizera-Neto; Teodiano Bastos
Journal:  Sensors (Basel)       Date:  2017-11-28       Impact factor: 3.576

2.  Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles.

Authors:  Quan Liu; Aiming Liu; Wei Meng; Qingsong Ai; Sheng Q Xie
Journal:  Front Neurorobot       Date:  2017-12-04       Impact factor: 2.650

3.  Learning to shape virtual patient locomotor patterns: internal representations adapt to exploit interactive dynamics.

Authors:  Christopher J Hasson; Sarah E Goodman
Journal:  J Neurophysiol       Date:  2018-11-07       Impact factor: 2.714

4.  New Motion Intention Acquisition Method of Lower Limb Rehabilitation Robot Based on Static Torque Sensors.

Authors:  Yongfei Feng; Hongbo Wang; Luige Vladareanu; Zheming Chen; Di Jin
Journal:  Sensors (Basel)       Date:  2019-08-06       Impact factor: 3.576

5.  Prediction Algorithm of Parameters of Toe Clearance in the Swing Phase.

Authors:  Tamon Miyake; Masakatsu G Fujie; Shigeki Sugano
Journal:  Appl Bionics Biomech       Date:  2019-08-14       Impact factor: 1.781

6.  Assessment of an Assistive Control Approach Applied in an Active Knee Orthosis Plus Walker for Post-Stroke Gait Rehabilitation.

Authors:  Ana Cecilia Villa-Parra; Jessica Lima; Denis Delisle-Rodriguez; Laura Vargas-Valencia; Anselmo Frizera-Neto; Teodiano Bastos
Journal:  Sensors (Basel)       Date:  2020-04-26       Impact factor: 3.576

7.  Configuration-Dependent Optimal Impedance Control of an Upper Extremity Stroke Rehabilitation Manipulandum.

Authors:  Borna Ghannadi; Reza Sharif Razavian; John McPhee
Journal:  Front Robot AI       Date:  2018-11-01

8.  Voluntary-Driven Elbow Orthosis with Speed-Controlled Tremor Suppression.

Authors:  Gil Herrnstadt; Carlo Menon
Journal:  Front Bioeng Biotechnol       Date:  2016-03-31

9.  Iterative Learning Impedance for Lower Limb Rehabilitation Robot.

Authors:  Chenhui Guo; Shuai Guo; Jiancheng Ji; Fengfeng Xi
Journal:  J Healthc Eng       Date:  2017-08-01       Impact factor: 2.682

Review 10.  Recent developments and challenges of lower extremity exoskeletons.

Authors:  Bing Chen; Hao Ma; Lai-Yin Qin; Fei Gao; Kai-Ming Chan; Sheung-Wai Law; Ling Qin; Wei-Hsin Liao
Journal:  J Orthop Translat       Date:  2015-10-17       Impact factor: 5.191

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