Development of Brain-Computer Interface Technology Using Scalp Electroencephalography

Abstract

Studies on electroencephalography-based brain computer interface (EEG-based BCI) has been widely studied since around 2000. In the studies, three methods, event-related desynchronization/synchronization (ERD/ERS) during a motor imagery task, a P300 component of event-related potential, and steady state visual evoked potential (SSVEP) has been studied as standard methods. Since around 2013, with the acceleration of research in the United States and other countries, there has been a wide variety of studies that is not limited to the standard methods, such as research and development toward practical application and studies on extracting new brain activity signals. Some of the research results have been developed as commercial products. In this paper, after reviewing the studies on EEG-based BCI, topics in the research and development toward practical application such as new EEG systems and artifact rejection methods are introduced, topics in the studies on extracting new brain activity signals such as applying deep learning, emotion estimation and visual image reconstruction are also introduced, and topics in combination of BCI and information and communications technology and combination of BCI and XR technology are introduced. Finally, prospects of BCI technology are discussed.