Yilun Chen

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About

Yilun Chen is an emerging researcher at the intersection of rehabilitation engineering, human-machine interaction, and biomedical systems. His work focuses on leveraging cutting-edge technologies to improve outcomes for individuals recovering from neurological conditions, particularly stroke. Chen's most notable contribution involves the application of digital twin technology to stroke rehabilitation, where he developed a framework for real-time, personalized patient evaluation that bridges the gap between short-term motor adaptation and long-term functional recovery. By virtually mirroring a patient's physical state and performance, his approach enables clinicians to customize rehabilitation tasks with unprecedented precision, potentially transforming how recovery protocols are designed and delivered. This work, published in 2023 and already accumulating citations within its first year, signals growing recognition from the broader rehabilitation and biomedical engineering communities. Chen's research reflects a forward-thinking integration of computational modeling and clinical practice, positioning him as a promising voice in the movement toward data-driven, individualized rehabilitation medicine. Students and researchers working in wearable systems, neurorehabilitation, or digital health will find his contributions particularly relevant and timely.