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부정감성 인식을 위한 생체신호 기반의 특징 선택 알고리즘 개발

Other Titles
 Feature Selecting Algorithm Development Based on Physiological Signals for Negative Emotion Recognition 
Authors
 이지은  ;  유선국 
Citation
 Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지), Vol.14(8) : 3925-3932, 2013 
Journal Title
 Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지) 
ISSN
 1975-4701 
Issue Date
2013
Keywords
Physiological Signal ; Emotion ; GA ; LDA
Abstract
Emotion is closely related to the life of human, so has effect on many parts such as concentration, learning ability, etc. and makes to have different behavior patterns. The purpose of this paper is to extract important features based on physiological signals to recognize negative emotion. In this paper, after acquisition of electrocardiography(ECG), electroencephalography(EEG), skin temperature(SKT) and galvanic skin response(GSR) measurements based on physiological signals, we designed an accurate and fast algorithm using combination of linear discriminant analysis(LDA) and genetic algorithm(GA), then we selected important features. As a result, the accuracy of the algorithm is up to 96.4% and selected features are Mean, root mean square successive difference(RMSSD), NN intervals differing more than 50ms(NN50) of heart rate variability(HRV), σand α frequency power of EEG from frontal region, α, β, and γfrequency power of EEG from central region, and mean and standard deviation of SKT. Therefore, the features play an important role to recognize negative emotion.
Full Text
http://dx.doi.org/10.5762/KAIS.2013.14.8.3925
Files in This Item:
T201303552.pdf Download
DOI
10.5762/KAIS.2013.14.8.3925
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Medical Engineering (의학공학교실) > 1. Journal Papers
Yonsei Authors
Yoo, Sun Kook(유선국) ORCID logo https://orcid.org/0000-0002-6032-4686
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/88163
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