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Gait Training Algorithm of an End-Effector Typed Hybrid Walking Rehabilitation Robot

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Abstract

The present study focused on the gait training algorithm of an end-effector typed hybrid walking rehabilitation robot that our research group developed in 2017. One motor and five link mechanism in the end-effector typed hybrid walking rehabilitation robot were used to mimic normal gait patterns. Depending on patients’ condition and training difficulty, three gait rehabilitation training modes were proposed. Mode 1 is a passive mode that motor leads to patients’ walking entirely, Mode 2 is an assisted-active mode that a part of patients’ muscle strength were supported depending on their walking intention, and Mode 3 is an active mode that patients walk on their own muscle strength under gait resistance by eddy current brake. At each training mode, patients’ muscle strength performance by driving motor was experimentally verified using electromyography. In addition, gait symmetry between injured limb and uninjured limb improved as evidenced by motion capture analysis using inertial measurement unit.

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Acknowledgements

This study was supported by the Translational Research Center for Rehabilitation Robots (NRCTR-EX17013). IRB No.: NRC-2017-04-029. In addition, this work was supported by Incheon National University (International Cooperative) Research Grant in 2018.

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Authors and Affiliations

  1. Department of Mechanical System Design Engineering, Seoul National University of Science and Technology, Seoul, 01811, South Korea

    Jung-Yup Kim & Jung-Joon Kim

  2. Department of Mechatronics Engineering, Incheon National University, Incheon, 22012, South Korea

    Kiwon Park

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  1. Jung-Yup Kim
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  2. Jung-Joon Kim
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  3. Kiwon Park
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Correspondence to Kiwon Park.

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Kim, JY., Kim, JJ. & Park, K. Gait Training Algorithm of an End-Effector Typed Hybrid Walking Rehabilitation Robot. Int. J. Precis. Eng. Manuf. 20, 1767–1775 (2019). https://doi.org/10.1007/s12541-019-00185-y

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  • DOI: https://doi.org/10.1007/s12541-019-00185-y

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