The application of machine-learning on lower limb motion analysis in human exoskeleton system
ICSR'12 Proceedings of the 4th international conference on Social Robotics
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Exoskeletons are attracting a great attention as a new means of rehabilitation devices. In such applications, control algorithms of exoskeletons are often inspired by nature for natural and effective assistance for patients. In this paper, a control algorithm is inspired by aquatic therapy. Aquatic therapy has various benefits for rehabilitation processes based on useful properties of water, e.g. buoyancy and drag. However, realization of such effects is challenged by limitations in hardware, such as mechanical impedance or impreciseness of actuator forces. Therefore, the resistive forces generated by actuators, which cause serious discomfort to patients, are precisely modeled and compensated to realize the control algorithm inspired by aquatic therapy effectively. The proposed methods are implemented in SUBAR developed by Sogang University and verified by experiments.