A Review on EEG Signals Based Emotion Recognition
Author(s) -
Morteza Zangeneh Soroush,
Keivan Maghooli,
Seyed Kamaledin Setarehdan,
Ali Motie Nasrabadi
Publication year - 2017
Publication title -
international clinical neuroscience journal
Language(s) - English
Resource type - Journals
eISSN - 2383-2096
pISSN - 2383-1871
DOI - 10.15171/icnj.2017.01
Subject(s) - electroencephalography , emotion recognition , brain–computer interface , computer science , emotion classification , field (mathematics) , affective computing , cognitive psychology , artificial intelligence , speech recognition , psychology , neuroscience , pure mathematics , mathematics
Emotion recognition has become a very controversial issue in brain-computer interfaces (BCIs). Moreover, numerous studies have been conducted in order to recognize emotions. Also, there are several important definitions and theories about human emotions. In this paper we try to cover important topics related to the field of emotion recognition. We review several studies which are based on analyzing electroencephalogram (EEG) signals as a biological marker in emotion changes. Considering low cost, good time and spatial resolution, EEG has become very common and is widely used in most BCI applications and studies. First, we state some theories and basic definitions related to emotions. Then some important steps of an emotion recognition system like different kinds of biologic measurements (EEG, electrocardiogram [EEG], respiration rate, etc), offline vs online recognition methods, emotion stimulation types and common emotion models are described. Finally, the recent and most important studies are reviewed.
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