Xueqiang Zhu

Papers

Total Citations

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About

Xueqiang Zhu is a researcher focused on rehabilitation robotics and sensor-based training systems, with a particular emphasis on improving motor recovery for patients with limb impairments. Their most cited work, "A Training Method for a Sensor-Based Exercise Rehabilitation Robot" (2022, 4 citations), addresses critical limitations in traditional mirror therapy by integrating real-time sensor feedback to enhance the effectiveness of rehabilitation exercises. Zhu proposed a mirror active rehabilitation training system that dynamically adapts to the patient's affected limb recovery, offering a more responsive and personalized approach to therapy. This contribution bridges the gap between conventional rehabilitation methods and modern robotic assistance, aiming to improve patient outcomes through continuous monitoring and adaptive training. While their citation count is currently modest, Zhu's work represents an important step in advancing sensor-driven, patient-centered rehabilitation technologies, with potential applications in clinical and home-based settings. Their research underscores a commitment to merging engineering innovation with practical therapeutic solutions, making it relevant for students and researchers interested in assistive robotics, human-robot interaction, and neurorehabilitation.