[2017]The effect of social intelligence levels on EEG band during watching emotional expression of avatar

2018-02-22
조회수 1193

Abstract

 Social intelligence is an important factor to understand other’s emotion in the relationship between individuals. Social intelligence has been tried to be evaluated qualitatively. However, it has been dependent on off-line analysis of subjective experience although emotion reaction has been required to be monitored in real time during interaction. This study was to determine social intelligence by measuring and analyzing EEG(Electroencephalogram) in real time. Forty-eight university students aged 20 to 31 (Mean = 23.96, SD = 2.84) years were asked to answer the Tromso Social Intelligence Scale. The social intelligence was divided into three levels according to the total scores of questionnaires. The tasks for simulating different social intelligence were to watch avatar animations with expressing positive and negative emotions respectively. The EEG was measured to 19 channels by international 10-20 systems. EEG spectrum extracted RFA(Relative Fast Alpha), RB(Relative Beta), RMB(Relative Mid Beta), RHB(Relative High Beta), RG(Relative Gamma), etc. One-way ANOVA analyzed the mean difference of EEG frequency variation according to social intelligence levels. The power of RMB on frontal (F7), RB, RMB, RFA, and RG on temporal (T3, T4, T5, and T6) and RG on occipital (O2) lobes showed significant difference among levels in positive emotion. The power of RMB on frontal (F4), RHB on temporal (T4), and RMB on occipital (O2) lobes showed significant difference among levels in negative emotion. These results expect to basic data to develop a social intelligence evaluation tool that can classify social intelligence level in real time by EEG response.


Keywords

Social intelligence, EEG , Valence


Reference

Seong-Eon Park, Min-Cheol Whang, Jung-Nyun Lee, Min-Ji Park, & Eric Che. (2017). The effect of social intelligence levels on EEG band during watching emotional expression of avatar. ICES 2017.