Po‐Lei Lee

About

Dr. Po‑Lei Lee is a leading innovator in brain‑computer interface (BCI) technology and neural rehabilitation engineering. His research focuses on decoding electroencephalography (EEG) signals to create intuitive, real‑world assistive devices. Dr. Lee’s most influential work, “A Brain‑Wave‑Actuated Small Robot Car Using Ensemble Empirical Mode Decomposition‑Based Approach” (2012, 59 citations), introduced a novel EEMD‑based method to extract steady‑state visual evoked potentials (SSVEPs). By enabling a user to wirelessly control a small robot car through three flickering visual stimuli (13, 14, and 15 Hz), this study demonstrated a practical, high‑speed BCI system that bypasses traditional muscle‑based control—a foundational contribution to hands‑free robotics. More recently, his 2025 paper on an EEG‑driven dual‑path fuzzy neural network‑controlled pneumatic exoskeleton for upper limb rehabilitation (2 citations) extends this expertise into neurorehabilitation, merging adaptive fuzzy control with pneumatic actuation to assist stroke survivors. Dr. Lee’s work uniquely bridges signal processing, machine learning, and mechanical design, offering scalable solutions for both assistive robotics and clinical therapy. His research continues to shape how neural signals can directly empower human‑machine interaction.

Research Focus

Key Achievements

Top Papers

1. 1
   A Brain-Wave-Actuated Small Robot Car Using Ensemble Empirical Mode Decomposition-Based Approach

   59 citations · 2012
2. 2
   Designing an EEG Signal-Driven Dual-Path Fuzzy Neural Network-Controlled Pneumatic Exoskeleton for Upper Limb Rehabilitation

   2 citations · 2025

Key Collaborators

Contact & Links