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Personality Trait and Facial Expression Filter-Based Brain-Computer Interface
Author(s) -
Seongah Chin,
Chung-Yeon Lee
Publication year - 2013
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/55665
Subject(s) - extraversion and introversion , computer science , personality , trait , filter (signal processing) , big five personality traits , facial expression , artificial intelligence , interface (matter) , cognitive psychology , computer vision , psychology , social psychology , bubble , maximum bubble pressure method , parallel computing , programming language
In this paper, we present technical approaches that bridge the gap in the research related to the use of brain‐computer interfaces for entertainment and facial expressions. Such facial expressions that reflect an individual’s personal traits can be used to better realize artificial facial expressions in a gaming environment based on a brain‐computer interface. First, an emotion extraction filter is introduced in order to classify emotions on the basis of the users’ brain signals in real time. Next, a personality trait filter is defined to classify extrovert and introvert types, which manifest as five traits: very extrovert, extrovert, medium, introvert and very introvert. In addition, facial expressions derived from expression rates are obtained by an extrovert‐introvert fuzzy model through its defuzzification process. Finally, we confirm this validation via an analysis of the variance of the personality trait filter, a k‐fold cross validation of the emotion extraction filter, an accuracy analysis, a user study of facial synthesis and a test case game

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