Information Science: human Interfaces, Inteligent systems

1. Brain-Computer Interfaces (BCIs) using EEG
－BCIs for prediction of movement information
−BCIs using Virtual Sounds
－Machine learning, feature selection, and neural network analysis for improvement of the BCI performance
2. Signal processing for functional near-infrared spectroscopy (fNIRS)and its application to BCIs
－Systemic artiface removal from short-distance channels
−fNIRS-BCIs for prediction of movement information
3．Human motor control, motor learning, and myoelectric interfaces
－Muscle synergy analysis during reachnig movements
−Prediction of movements from muscle activities
4. Virtual Sound synthesis
− Individualization of the head-related transfer functions

1．Electroencephalogram （BioSemi）
2．Myoelectric measuremet system（Delsys, OTbio）

1. Machine learning for biosignals
2. Brain imaging using EEG and fNIRS

１．Human Interfaces and Brain-Computer Interfaces
２．Machine learning
３．Neuroimaging (assistive technology and rehabilitation techniques)

We aim to examine fundermentals for new interfaces in the future based on non-invasive brain imaging and machine learning techniques applicable to the biosignals.