Papers
1
Total Citations
7
H-Index
1
About
Yong Ding is a researcher working at the intersection of rehabilitation engineering, computer vision, and machine learning, with a particular focus on improving outcomes for stroke patients undergoing robot-assisted therapy. His most recognized work addresses one of the persistent challenges in neurorehabilitation: the automatic detection of compensatory postures that stroke patients often adopt during upper-extremity recovery exercises. These compensatory movements, while allowing task completion, can undermine long-term neurological recovery if left unaddressed by clinicians. In his 2020 pilot study on reaching movement, Ding demonstrated the feasibility of using vision-based systems combined with kinematic data and machine learning algorithms to identify such postures in real time — a meaningful step toward smarter, more responsive rehabilitation robotics. With 7 citations, this work has begun attracting attention from the rehabilitation and human-computer interaction communities. By bridging clinical insight with advanced sensing and data-driven methods, Ding's research holds promise for developing autonomous monitoring tools that could enhance the quality and precision of stroke rehabilitation, potentially reducing clinician burden while personalizing patient care at scale.
Research Focus
Key Achievements
Top Papers
- 1