Seungheon Chae
Papers
2
Total Citations
6
H-Index
2
About
Seungheon Chae is a rising figure in robotics and rehabilitation engineering, whose work bridges intelligent automation and human–machine interaction. His primary research areas include robotic surface finishing, exoskeletal rehabilitation systems, and transfer learning for motion intention detection. In his 2024 study on sanding robots, Chae introduced an experimental design for a 4-point supported belt robot tailored to large convex surfaces—a novel approach that addresses the longstanding challenges of prolonged working time and uneven sanding quality in large-area finishing tasks. This work has already garnered attention with 3 citations, signaling its practical relevance to manufacturing automation. In parallel, Chae made a significant contribution to rehabilitation robotics by proposing an improved transfer learning framework that detects upper-limb movement intentions using mechanical sensors—including sEMG, force-sensitive resistors, and inertial measurement units—within an exoskeletal system. This innovation enhances the adaptability and responsiveness of assistive devices, offering new possibilities for personalized therapy. With both papers published in 2024, Chae’s early-career output demonstrates a clear trajectory toward impactful, application-driven research that stands to influence both industrial robotics and clinical rehabilitation technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2