Emotional brain-computer interface

A Brain-Computer interface (BCI) is defined as a communication system in which the messages that the user wants to send to the external world do not pass through the normal pathways of nerves and muscles but are directly extracted from her/his brain activity which is monitored in real-time.

BCIs are functionally divided into three subsystems, namely signal acquisition, translation into commands, and application. Most efforts have been directed towards increasing the information throughput of BCI systems by optimizing the operation of the second and third subsystems using sophisticated signal processing and machine learning algorithms. In spite of such efforts, current BCI systems report bit-rates lower than 100 bits-per-minute. In addition, BCI illiteracy is estimated to affect 20-40% of the population.

A recent trend in BCI technology aims at utilizing the unique feature of BCIs, namely their ability to access the user’s brain activity in order to determine the user’s affective state. Such knowledge may constitute the key for increasing the information throughput and reducing BCI illiteracy.

In this tutorial talk, the BCI concept is first introduced and the operation of the three main types of noninvasive BCIs (i.e. P300, ERD/ERS, and SSVEP based BCIs) is presented in detail. The electroencephalogram (EEG) patterns that characterize emotional states are then reviewed. In particular, the EEG correlates of emotional arousal and valence. The influence of the emotional state in the relevant signals for BCI operation is presented. Concrete proposals utilizing the user’s affective state to enhance BCI operation are then discussed in detail.