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Neural Network Based Emotion Estimation Using Heart Rate Variability and Skin Resistance

Authors
 Sun K. Yoo  ;  Chung K. Lee  ;  Youn J. Park  ;  Nam H. Kim  ;  Byung C. Lee  ;  Kee S. Jeong 
Citation
 Lecture Notes in Computer Science, Vol.3610(PART I) : 818-824, 2005-06 
Journal Title
 Lecture Notes in Computer Science 
ISSN
 0302-9743 
Issue Date
2005-06
Keywords
Heart Rate Variability ; Autonomic Nervous System ; Galvanic Skin Response ; Autonomic Nervous System Activity ; Trained Neural Network
Abstract
In order to build a human-computer interface that is sensitive to a user’s expressed emotion, we propose a neural network based emotion estimation algorithm using heart rate variability (HRV) and galvanic skin response (GSR). In this study, a video clip method was used to elicit basic emotions from subjects while electrocardiogram (ECG) and GSR signals were measured. These signals reflect the influence of emotion on the autonomic nervous system (ANS). The extracted features that are emotion-specific characteristics from those signals are applied to an artificial neural network in order to recognize emotions from new signal collections. Results show that the proposed method is able to accurately distinguish a user’s emotion.
Full Text
https://link.springer.com/chapter/10.1007/11539087_110
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Medical Engineering (의학공학교실) > 1. Journal Papers
Yonsei Authors
Kim, Nam Hyun(김남현)
Yoo, Sun Kook(유선국) ORCID logo https://orcid.org/0000-0002-6032-4686
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/178849
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