Chung-Min Wu

About

Chung-Min Wu is a leading researcher in brain-computer interfaces (BCI), with a focus on steady-state visual evoked potentials (SSVEP) and fuzzy logic systems. His work centers on developing practical, single-channel SSVEP-based BCI systems that can be integrated into assistive technologies, particularly for individuals with motor neuron diseases. Wu’s most notable contributions include the creation of a fuzzy feature threshold algorithm that enhances the accuracy and reliability of single-channel BCI systems, as demonstrated in his 2017 paper (39 citations), which applied this algorithm to control a maze game. He also pioneered the use of SSVEP-based BCIs for automatic feeding robots (18 citations) and mobile robot navigation in maze games (15 citations), directly aiming to improve quality of life for users with severe motor impairments. By combining fuzzy decision-making with SSVEP technology, Wu has advanced the field of assistive robotics, offering intuitive, non-invasive control interfaces. His work, though modest in citation counts, represents a significant step toward practical, low-cost BCI applications for real-world assistive scenarios.

Research Focus

Key Achievements

Top Papers

1. 1
   A Single-Channel SSVEP-Based BCI with a Fuzzy Feature Threshold Algorithm in a Maze Game

   39 citations · 2017
2. 2
   Applying fuzzy decision for a single channel SSVEP-based BCI on automatic feeding robot

   18 citations · 2016
3. 3
   A new SSVEP based BCI application on the mobile robot in a maze game

   15 citations · 2016

Key Collaborators

Contact & Links