From neuroscience to neurotechnology: The decoding of brain information and its application by Neurocommunicator

Abstract

Neurotechnology, which is the application of neuroscience, offers us tools and services to better understand and improve brain functions. The Brain-Machine Interface (BMI) or Brain-Computer Interface (BCI) is a good example of Neurotechnology. BMI enables direct communication between the brain and external devices. BMIs are classified as invasive and non-invasive types. Electroencephalography (EEG)-based BMIs have advantages in their low cost, safety and portability even though they have limited controls. The author and his coworkers have been developing a cognitive BMI, the “Neurocommunicator” to support communication with people with severe motor disabilities. The system can predict a user’s decision about a message to be expressed by his/her CG avatar. This prediction is based on a real-time analysis of EEG data, especially event-related potentials (ERPs) such as P300. The system is currently being tested by patients in an at-home setting with a final goal of developing a commercial product. Recently, a new trial has begun, in which the patient can use a humanoid robot as his/her avatar. This BMI-controlled robot avatar would then express the user’s emotions with dynamic gestures. It would also interact with the real world on behalf of the users even in remote places.