Papers
6
Total Citations
307
H-Index
5
About
Dr. Jer-Junn Luh is a leading figure in rehabilitation robotics and biomedical signal processing, whose work has profoundly advanced the technology behind assistive systems for stroke recovery and motor impairment. His research primarily focuses on the development of intelligent upper-limb rehabilitation robots and the decoding of human motion intent through electromyography (EMG) signals. Dr. Luh’s most impactful contribution is his pioneering work on assistive control systems for rehabilitation robots, as detailed in his highly cited 2016 paper (110 citations), which introduced a dynamic human model and force/torque sensors to simulate natural patient-robot interaction across active, assistive, and passive modes. He has also made significant strides in motion pattern recognition, notably developing a novel STFT-ranking feature for multi-channel EMG (100 citations) and conducting comparative studies on dynamic versus isometric muscle contractions (74 citations). His work on arm exoskeleton rehabilitation robots (2012) further established key kinematic structures and assistive control strategies that improve rehabilitation quality and enable quantitative recovery assessment. Through these innovations, Dr. Luh has helped bridge the gap between robotic assistance and human physiology, creating more responsive, adaptive, and effective rehabilitation tools that are widely cited and built upon by researchers worldwide.
Research Focus
Key Achievements
Top Papers
- 1Assistive Control System for Upper Limb Rehabilitation Robot110 citations · 2016
- 2A novel STFT-ranking feature of multi-channel EMG for motion pattern recognition100 citations · 2014
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- 6A joint localizer for finger length measurements3 citations · 2013