Yinan Jin

University of Canberra, Zhejiang University of Technology

Papers

Total Citations

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About

Yinan Jin is a rising researcher at the intersection of rehabilitation robotics and intelligent control systems. His primary research focuses on developing compliant, multi-degree-of-freedom robotic devices for gait rehabilitation, where he addresses critical challenges in mechanism design and human-robot interaction. Jin’s most cited work, “Design and analysis of a multi-DOF compliant gait rehabilitation robot” (2023, 8 citations), pioneers non-ergonomic solutions that reduce cardiorespiratory load during therapy—a significant advancement for patient comfort and treatment efficacy. He has further pushed boundaries in biosignal processing with “Complete Gait Phase Recognition Based on Muscle Synergy Using PSO-CNN-LSTM Algorithm” (2025), which achieves precise recognition of seven gait phases during continuous walking, enabling more adaptive rehabilitation protocols. His contributions extend to nonlinear model predictive control for self-aligning compliant robots and hierarchical control architectures for fully-driven dexterous hands inspired by human tendon structures. By integrating compliant mechanisms with advanced AI-driven control, Jin’s work directly improves the safety, adaptability, and clinical outcomes of robotic rehabilitation. With recent publications in 2023-2025, his research trajectory signals a deep commitment to translating biomechanical insights into practical, patient-centered robotic systems.