Using neural network to recognize human emotions from heart rate variability and skin resistance.
The purpose of this paper is to estimate emotions using Neural network and the changes in activities of autonomic nervous system(ANS). Since ANS cannot be controlled artificially, we presumed that the changes in emotions would be reflected to the changes in ANS. In order to observe those changes, we provided the subjects with some video clips which can induce a variety of emotions and measured the changes in ANS, especially in Heart Rate Variability(HRV) and in Galvanic Skin Response(GSR). With those analyzed results from the experiments, we established an algorithm based on Neural network, finally we could reach the estimating rate of 80.2%
Lee
Chung
C
Yonsei University, Seoul, Korea (phone: 822-222-81922; fax: 822-361-9923; e-mail: nolegal@yumc.yonsei.ac.kr).
Yoo
S K
SK
Park
Yoonj
Y
Kim
Namhyun
N
Jeong
Keesam
K
Lee
Byungchae
B