Yurong Li
Papers
5
Total Citations
124
H-Index
5
About
Dr. Yurong Li is a leading researcher in intelligent human-robot interaction and rehabilitation engineering, with a focus on decoding human motion intent for advanced prosthetic and exoskeleton control. Her work centers on developing artificial neural network (ANN) models and transfer learning techniques to predict lower extremity joint moments and decode muscle activity from surface electromyography (sEMG) signals. A key contribution is her pioneering approach to predicting human joint moments using only online measurable input variables, eliminating the need for specialized kinetic measurement equipment—a breakthrough that makes rehabilitation assessment more accessible and cost-effective. Her most cited paper (2019, 58 citations) demonstrates an ANN-based method for intelligent joint moment prediction, while her transfer learning framework (2021, 24 citations) enables low-cost, wearable sEMG decoding. Dr. Li has also advanced discrete hand motion intention decoding within electromechanical delay constraints, enhancing real-time human-robot interaction. Her comprehensive survey on rehabilitation robot control strategies (2022) further underscores her role in shaping the field. With over 120 total citations, Dr. Li’s research is instrumental in bridging machine learning and biomechanics for practical, low-cost rehabilitation technologies.
Research Focus
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Top Papers
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