Wei-Keung Lee

About

Wei-Keung Lee is a leading researcher in rehabilitation robotics and intelligent control systems, with a focus on integrating biomedical signal processing and soft robotics for upper limb recovery. His most-cited work, "Designing an EEG Signal-Driven Dual-Path Fuzzy Neural Network-Controlled Pneumatic Exoskeleton for Upper Limb Rehabilitation" (2025), exemplifies his innovative approach to combining electroencephalography (EEG) with fuzzy neural network control to create adaptive, brain-driven exoskeletons. This dual-path architecture allows for real-time, intuitive assistance during rehabilitation, significantly enhancing patient engagement and motor recovery outcomes. While his citation count is still growing, Lee’s contributions are already recognized for pushing the boundaries of human-machine interfaces and neurorehabilitation. His work bridges the gap between neural decoding and pneumatic actuation, offering a scalable, non-invasive solution for stroke and injury patients. Lee’s research holds promise for transforming clinical rehabilitation practices, making him a rising figure in assistive robotics and neural control systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Designing an EEG Signal-Driven Dual-Path Fuzzy Neural Network-Controlled Pneumatic Exoskeleton for Upper Limb Rehabilitation

   2 citations · 2025

Key Collaborators

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