Editorial:
Special Issue on Brain Machine/Computer Interface and its Application
Shoichiro Fujisawa, Minoru Fukumi, Jianting Cao, Yasue Mitsukura, and Shin-ichi Ito
Professor, Faculty of Science and Engineering, Tokushima Bunri University
1314-1 Shido, Sanuki-shi, Kagawa 769-2193, Japan
Professor, Graduate School of Technology, Industrial and Social Sciences, Tokushima University
2-1 Minami-josanjima, Tokushima 770-8506, Japan
Professor, Department of Information Systems, Saitama Institute of Technology
1690 Fusaiji, Fukaya, Saitama 369-0203, Japan
Professor, Department of System Design Engineering, Keio University
3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan
Associate Professor, Graduate School of Technology, Industrial and Social Sciences, Tokushima University
2-1 Minami-josanjima, Tokushima 770-8506, Japan
Brain machine/computer interface (BMI/BCI) technologies are based on analyzing brain activity to control machines and support the communication of commands and messages. To sense brain activities, a functional NIRS and electroencephalogram (EEG) that has been developed for that purpose is often employed. Analysis techniques and algorithms for the NIRS and EEG signals have also been created, and human support systems in the form of BMI/BCI applications have been developed. In the field of rehabilitation, BMI/BCI is used to control environment control systems and electric wheelchairs. In medicine, BMI/BCI is used to assist in communications for patient support. In industry, BMI/BCI is used to analyze sensibility and develop novel games.
This special issue on Brain Machine/Computer Interface and its Application includes six interesting papers that cover the following topics: an EEG analysis method for human-wants detection, cognitive function using EEG analysis, auditory P300 detection, a wheelchair control BCI using SSVEP, a drone control BMI based on SSVEP that uses deep learning, and an improved CMAC model.
We thank all authors and reviewers of the papers and the Editorial Board of Journal of Robotics and Mechatronics for its help with this special issue.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.