Wangyang Ge

Shandong Institute of Automation, China University of Geosciences

Papers

Total Citations

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About

Wangyang Ge is a researcher focused on advancing rehabilitation robotics, with a particular emphasis on lower-limb assistive technologies. Their work integrates mechanical design, control systems, and intelligent algorithms to improve patient outcomes during physical therapy. Ge’s most cited paper, "Experimental Design of Lower-limb Movement Recognition Based on Support Vector Machine" (2022, 7 citations), introduces a machine learning approach to accurately identify patient movements, enabling more responsive and personalized robotic assistance. In "Rehabilitation Evaluation System for Lower-Limb Rehabilitation Robot" (2023, 3 citations), Ge addresses the critical need for objective, robot-integrated assessment methods to track patient progress over long training periods. Their comprehensive review, "Mechanical Structure and Control Methods for Lower-Limb Rehabilitation Robots" (2021, 2 citations), provides a valuable taxonomy of commercial systems and their underlying control strategies. Collectively, Ge’s contributions bridge the gap between robotic hardware and patient-centric evaluation, offering practical frameworks for active training and recovery monitoring. This work holds significant potential for enhancing the efficacy of rehabilitation programs for individuals with lower-limb impairments.