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@article{ART002247111},
author={Sung-Soo Park and Kun-Chang Lee},
title={Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2017},
volume={22},
number={7},
pages={75-82},
doi={10.9708/jksci.2017.22.05.075}

TY - JOUR
AU - Sung-Soo Park
AU - Kun-Chang Lee
TI - Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements
JO - Journal of The Korea Society of Computer and Information
PY - 2017
VL - 22
IS - 7
PB - The Korean Society Of Computer And Information
SP - 75
EP - 82
SN - 1598-849X
AB - Correct prediction of emotion is essential for developing advanced health devices. For this purpose, neural network has been successfully used. However, interpretation of how a certain emotion is predicted through the emotion prediction neural network is very tough. When interpreting mechanism about how emotion is predicted by using the emotion prediction neural network can be developed, such mechanism can be effectively embedded into highly advanced health-care devices. In this sense, this study proposes a novel approach to interpreting how the emotion prediction neural network yields emotion. Our proposed mechanism is based on HRV (heart rate variability) measurements, which is based on calculating physiological data out of ECG (electrocardiogram) measurements. Experiment dataset with 23 qualified participants were used to obtain the seven HRV measurement such as Mean RR, SDNN, RMSSD, VLF, LF, HF, LF/HF. Then emotion prediction neural network was modelled by using the HRV dataset. By applying the proposed mechanism, a set of explicit mathematical functions could be derived, which are clearly and explicitly interpretable. The proposed mechanism was compared with conventional neural network to show validity.
KW - emotion prediction;HRV(heart rate variability);neural network;inference process interpretation;healthcare devices
DO - 10.9708/jksci.2017.22.05.075
ER -

Sung-Soo Park and Kun-Chang Lee. (2017). Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements. Journal of The Korea Society of Computer and Information, 22(7), 75-82.

Sung-Soo Park and Kun-Chang Lee. 2017, "Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements", Journal of The Korea Society of Computer and Information, vol.22, no.7 pp.75-82. Available from: doi:10.9708/jksci.2017.22.05.075

Sung-Soo Park, Kun-Chang Lee "Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements" Journal of The Korea Society of Computer and Information 22.7 pp.75-82 (2017) : 75.

Sung-Soo Park, Kun-Chang Lee. Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements. 2017; 22(7), 75-82. Available from: doi:10.9708/jksci.2017.22.05.075

Sung-Soo Park and Kun-Chang Lee. "Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements" Journal of The Korea Society of Computer and Information 22, no.7 (2017) : 75-82.doi: 10.9708/jksci.2017.22.05.075

Sung-Soo Park; Kun-Chang Lee. Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements. Journal of The Korea Society of Computer and Information, 22(7), 75-82. doi: 10.9708/jksci.2017.22.05.075

Sung-Soo Park; Kun-Chang Lee. Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements. Journal of The Korea Society of Computer and Information. 2017; 22(7) 75-82. doi: 10.9708/jksci.2017.22.05.075

Sung-Soo Park, Kun-Chang Lee. Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements. 2017; 22(7), 75-82. Available from: doi:10.9708/jksci.2017.22.05.075

Sung-Soo Park and Kun-Chang Lee. "Emotion prediction neural network to understand how emotion is predicted by using heart rate variability measurements" Journal of The Korea Society of Computer and Information 22, no.7 (2017) : 75-82.doi: 10.9708/jksci.2017.22.05.075