COGNITIVE RECOGNITION BASED ON EEG SIGNAL ANALYSIS

Abstract

Cognitive science is the interdisciplinary, scientific study of the mind and its processes. It is used to examine the nature, tasks, functions of cognition . we study intelligence and behaviour, with a focus on how nervous system represents, process, and transform information. Electroencephalography is an electrophysiological monitoring method to record electrical activity of the brain. It is typically non invasive, with the electrodes placed along the scalp. The DEAP(database for emotional analysis using physiological signals) data set give us the stimulus that is needed for the cognitive analysis by studying the emotional trends of a person. Though in DEAP data set many physiological signals are used but we will be keeping our discussion to the EEG signals only. Emotion refers to the changes in the psychological and physical state as a response to internal or external stimulus event, but there is no widespread consensus on the definition of emotion. Not just that, but also there is an overlapping among the concepts of emotion, feeling and mood. In our work we have used the multi fractal detrended fluctuation analysis (MFDFA) on EEG signals that we acquire from DEAP data set. Now we will do further analysis by calculating the features. These features are nothing but the mathematical modalities of our EEG signal that has been generated through 32 channels which is available to us already in the DEAP data set. Once these features are calculated we can get the idea what parameters are obtained for different channel, different frequency and different feature that we select by comparing them to each other.