Yangsoo Kim

Papers

1

Total Citations

7

H-Index

1

About

Yangsoo Kim is a researcher focused on the intersection of robotics, machine learning, and neurorehabilitation, with a particular emphasis on improving motor recovery for post-stroke patients. His work centers on developing intelligent systems that can autonomously assess and guide therapeutic exercises, reducing the need for constant therapist supervision. In his most-cited study, a preliminary investigation published in 2017, Kim introduced a novel classifier designed to evaluate movement quality during unassisted pick-and-place exercises using a service robot. This contribution is foundational for creating autonomous therapy sessions where robots can reinforce therapeutically desirable movements in real time. Although his citation count is still growing—with his top paper garnering 7 citations—the work represents an important step toward scalable, accessible rehabilitation technology. Kim’s research bridges engineering and clinical practice, aiming to make robot-assisted therapy more adaptive and effective. His efforts are particularly valuable for stroke survivors who require consistent, high-quality motor training to regain function, highlighting his commitment to translating technical innovation into tangible patient benefits.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Learning classifier to evaluate movement quality in unassisted pick-and-place exercises for post-stroke patients: A preliminary study
7 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 4

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago