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In this study, we propose an interaction control framework for gait assistance and resistance using a robotic exoskeleton. We define a smoothed state variable that represents joint angle movements while walking. Furthermore, a self-feedback controller is designed with the delayed output state. By applying an appropriate time-delay and positive or negative feedback gain to the state variable, we can generate assistive or resistive torque stably without any gait phase or environment recognition. The time-delayed selffeedback controller reflects the movement of the wearer's joints at every moment of control, thereby stably coping with sudden task transitions (e.g., walk-stop-walk, forward-backward walking) as well as walking speed or environment changes. Case studies involved gait assistance with a knee exoskeleton and gait assistance and resistance with a hip exoskeleton. We performed various preliminary tests including metabolic energy measurements and a comparison of the positive or negative power of the generated torque profiles. The results show the flexibility and effectiveness of the proposed interaction control method for gait assistive or resistive training.
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Lim et al. (2019) studied this question.
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