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Front. Neurorobot. | doi: 10.3389/fnbot.2019.00067

Development of an EMG-Controlled Knee Exoskeleton to Assist Home Rehabilitation in a Game Context

  • 1Beihang University, China
  • 2ETH Zürich, Switzerland

As a leading cause of loss of functional movement, stroke often makes it difficult for patients to walk. Interventions to aid motor recovery in stroke patients should be carried out as a matter of urgency. However, muscle activity in the knee is usually too weak to generate overt movements, which poses a challenge for early post-stroke rehabilitation training. Although electromyography (EMG)-controlled exoskeletons have the potential to solve this problem, most existing robotic devices in rehabilitation centers are expensive, technologically complex, and allow only low training intensity. To address these problems, we have developed an EMG-controlled knee exoskeleton for use at home to assist stroke patients in their rehabilitation. EMG signals of the subject are acquired by an easy-to-don EMG sensor and then processed by a Kalman filter to control the exoskeleton autonomously. A newly-designed game is introduced to improve rehabilitation by encouraging patients' involvement in the training process. Six healthy subjects took part in an initial test of this new training tool. The test showed that subjects could use their EMG signals to control the exoskeleton to assist them in playing the game. Subjects found the rehabilitation process interesting, and they improved their control performance through 20-block training, with game scores increasing from 41.3 ± 15.19 to 78.5 ± 25.2 . The setup process was simplified compared to traditional studies and took only 72 s according to test on one healthy subject. The time lag of EMG signal processing, which is an important aspect for real-time control, was significantly reduced to about 64~ms by employing a Kalman filter, while the delay caused by the exoskeleton was about 110 ms. This easy-to-use rehabilitation tool has a greatly simplified training process and allows patients to undergo rehabilitation in a home environment without the need for a therapist to be present. It has the potential to improve the intensity of rehabilitation and the outcomes for stroke patients in the initial phase of rehabilitation.

Keywords: electromyography (EMG), Game context, Home rehabilitation, human-computer interaction, Kalman filter, Knee exoskeleton, Stroke

Received: 25 Feb 2019; Accepted: 06 Aug 2019.

Edited by:

Zlatko Matjacic, University Rehabilitation Institute (Slovenia), Slovenia

Reviewed by:

Thomas C. Bulea, National Institutes of Health (NIH), United States
Asuka Takai, Advanced Telecommunications Research Institute International (ATR), Japan  

Copyright: © 2019 Lyu, Chen, Ding, Wang, Pei and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Weihai Chen, Beihang University, Beijing, China,