Takuya Tagami

About

Takuya Tagami is a pioneering researcher at the intersection of neuroscience, artificial intelligence, and assistive robotics. His primary research areas include brain-computer interfaces (BCIs), deep learning for EEG signal processing, and intelligent mobility systems for individuals with physical disabilities. Tagami's most notable contribution is the development of the Brain-Mobility-Interface (BMI), a system that allows users to mentally control a personal mobility robot (PMR) by decoding EEG signals. In his highly cited 2021 paper, he demonstrated how deep learning techniques can classify brain states and even detect user face direction from neural data, translating these signals into precise control commands for the PMR. This work, which has garnered 6 citations, represents a significant leap toward non-invasive, thought-driven assistive technology. By merging advanced neural decoding with real-world mobility applications, Tagami is helping to redefine independence for individuals with severe motor impairments. His research not only advances BCI robustness but also lays the groundwork for more intuitive human-robot interaction systems, making him a key figure in the future of neurorehabilitation and assistive robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Brain-Mobility-Interface based on Deep Learning Techniques for Classifying EEG Signals into Control Commands

   6 citations · 2021

Key Collaborators

Contact & Links