EEG-based Emotion Recognition Using Self-Organizing Map for Boundary Detection

Autor:	Kai Keng Ang, Hiok Chai Quek, Reza Khosrowabadi, Abdul Wahab
Rok vydání:	2010
Předmět:	Boundary detection Self-organizing map medicine.diagnostic_test Computer science Speech recognition Feature extraction medicine Valence (psychology) Electroencephalography Classifier (UML) Arousal
Zdroj:	ICPR
DOI:	10.1109/icpr.2010.1031
Popis:	This paper presents an EEG-based emotion recognition system using self-organizing map for boundary detection. Features from EEG signals are classified by considering the subjects’ emotional responses using scores from SAM questionnaire. The selection of appropriate threshold levels for arousal and valence is critical to the performance of the recognition system. Therefore, this paper investigates the performance of a proposed EEG-based emotion recognition system that employed self-organizing map to identify the boundaries between separable regions. A study was performed to collect 8 channels of EEG data from 26 healthy right-handed subjects in experiencing 4 emotional states while exposed to audio-visual emotional stimuli. EEG features were extracted using the magnitude squared coherence of the EEG signals. The boundaries of the EEG features were then extracted using SOM. 5-fold cross-validation was then performed using the k-nn classifier. The results showed that proposed method improved the accuracies to 84.5%.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a57d3530053ea6d6a54bd7c2e050c3bc https://doi.org/10.1109/icpr.2010.1031 Zobrazit plný text záznamu