Customized stiffness control strategy for a six-bar linkage-based gait rehabilitation robot

Kapsalyamov A. Hussain S. Goecke R. Brown N.A.T. Jamwal P.K.
1 October 2024 Cambridge University Press

Robotica
2024 #42 Issue 10 3398 - 3415 pp.

Lower limb rehabilitation robots based on linkage-based mechanisms have recently drawn significant attention in the field due to their numerous advantages. The control of previously proposed linkage-based gait rehabilitation robotic orthoses has been achieved using constant speed control without consideration for the interaction forces. However, such an approach can be harmful to people with stroke since the level of disability varies among individuals, and it may cause potential injuries when excessive force is applied by the robot. To overcome this limitation and improve the rehabilitation process, it is necessary to recognize the force exerted by the person during walking and adjust the robots assistive torque accordingly, to provide synchronized motion. Thus, in this work, a human-cooperative approach based on a stiffness control strategy for the six-bar linkage-based gait rehabilitation robot is presented. The proposed methodology can serve as a solid foundation for developing a human-cooperative approach for linkage-based lower limb rehabilitation robotic orthoses. The control was validated and tested with eight healthy human subjects. As a result, customized robotic assistance with this mechanism can be provided during training to meet the individual needs of stroke patients, which can lead to increased engagement and contribution, thus improving treatment outcomes.

gait training , robotic orthosis , stephenson III six-bar linkage , stiffness control

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Human-Centred Technology Research Centre, University of Canberra, Canberra, Australia
School of Systems and Computing, UNSW Canberra, Canberra, Australia
Faculty of Health, Queensland University of Technology, Brisbane, Australia
Department of Electrical and Computer Engineering, Nazarbayev University, Astana, Kazakhstan

Human-Centred Technology Research Centre
School of Systems and Computing
Faculty of Health
Department of Electrical and Computer Engineering

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