Soo-Hong Lee
Papers
3
Total Citations
42
H-Index
2
About
Soo-Hong Lee is a leading researcher in the field of rehabilitation robotics and human-robot interaction, with a primary focus on lower-limb exoskeleton systems. His work centers on developing intelligent control algorithms that enable exoskeletons to intuitively interpret and assist human movement, particularly for individuals with mobility impairments. Lee’s most significant contribution is his novel approach to estimating continuous joint angles—specifically the knee and ankle (talocrural and subtalar joints)—using neural networks, as detailed in his highly cited 2021 paper (35 citations). This work addresses the critical challenge of real-time movement intention detection, allowing exoskeletons to provide seamless mechanical assistance. Additionally, Lee has advanced the field by creating an ankle intention detection algorithm that translates electromyography (EMG) signals into user-desired torque, a key innovation for improving stability and natural gait. His research also includes the development of a multiple-motion mode switching robot platform, demonstrating his versatility in designing adaptive robotic systems. With a growing citation impact and a clear focus on practical, patient-centered solutions, Lee is establishing himself as an important voice in the future of assistive robotics and neural-controlled prosthetics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Ankle intention detection algorithm using electromyography signal5 citations · 2021
- 3Multiple-motion mode switching robot platform2 citations · 2019