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Project

Mental state change detection from EEG by using multi-channel information theoretic metrics.

Mental state change detection from EEG is a longstanding challenge in biomedical signal processing. We will concentrate, for the first time in this research area, on the EEG signal features based on information theoretic metrics that are potentially modulated by the subject's mental state changes (emotion, alertness, attention, etc). The proposed metrics open new perspectives for EEG-based mental state detection as they are strictly data-driven (no assumptions on the existence of EEG frequency bands or which electrodes to consider) and account for the possible presence of non-linear relations between the multi-channel EEG recordings.
Date:1 Oct 2012 →  30 Sep 2015
Keywords:EEG, Mental state, Information theory
Disciplines:Neurosciences, Biological and physiological psychology, Cognitive science and intelligent systems, Developmental psychology and ageing