Nowadays a large number of individuals suffer from lower-limb weaknesses caused by multiple reasons, such as the gradual degeneration of musculoskeletal structure in elderly population, and the pathological losses of neuromuscular functions in stroke and spinal cord injury patients. In this paper, the design and control of a new robotic knee orthosis is presented, with the objective of assisting the user’s locomotion (primarily sit-to-stand motion) by applying an assistive torque on the knee, the largest joint in the human body. The orthosis consists of an orthosis shell and an actuation unit. The former functions as the user interface that transfers the assistive torque to the human body, while the latter generates the desired assistive torque with a motor-ball screw assembly. Through detailed design calculation, it has been demonstrated that the actuated orthotic joint is able to provide 20% of the required knee torque in the sit-to-stand motion. A controller for the robotic orthosis has also been developed by studying and emulating the knee biomechanics in the sit-to-stand motion. Benchtop testing conducted on a surrogate limb system demonstrated that the joint motion powered by the robotic orthosis is stable, smooth, and similar to the biological knee motion in the human sit-to-stand motion.
- Dynamic Systems and Control Division
A Robotic Knee Orthosis for Sit-to-Stand Assistance
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Thapa, S, Zheng, H, Kogler, GF, & Shen, X. "A Robotic Knee Orthosis for Sit-to-Stand Assistance." Proceedings of the ASME 2016 Dynamic Systems and Control Conference. Volume 1: Advances in Control Design Methods, Nonlinear and Optimal Control, Robotics, and Wind Energy Systems; Aerospace Applications; Assistive and Rehabilitation Robotics; Assistive Robotics; Battery and Oil and Gas Systems; Bioengineering Applications; Biomedical and Neural Systems Modeling, Diagnostics and Healthcare; Control and Monitoring of Vibratory Systems; Diagnostics and Detection; Energy Harvesting; Estimation and Identification; Fuel Cells/Energy Storage; Intelligent Transportation. Minneapolis, Minnesota, USA. October 12–14, 2016. V001T07A004. ASME. https://doi.org/10.1115/DSCC2016-9891
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