Papers
5
Total Citations
279
H-Index
5
About
Jimson Ngeo is a leading researcher in the fields of myoelectric control, human-machine interaction, and assistive robotics. His work focuses on decoding complex human motor intentions—particularly from surface electromyography (EMG) signals—to enable natural, proportional control of robotic prostheses, exoskeletons, and virtual reality interfaces. Ngeo’s major contributions include pioneering methods for the continuous and simultaneous estimation of multi-degree-of-freedom finger kinematics from EMG, using advanced models such as muscle activation dynamics, multi-output Gaussian Processes, and nonlinear synergies in latent space representations. His most cited paper (199 citations) demonstrates a breakthrough in real-time finger motion estimation, while his research on cloth dynamics modeling and latent space learning extends into robotic clothing assistance. With over 270 total citations across his top works, Ngeo’s research has significantly advanced the practical deployment of myoelectric control systems, bridging the gap between biological signals and dexterous robotic manipulation. His work is essential reading for anyone interested in neural interfaces, rehabilitation engineering, and the future of intuitive human-robot collaboration.
Research Focus
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