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논문 기본 정보

자료유형
학술저널
저자정보
박성수 (Sungkyunkwan University) 이건창 (Sungkyunkwan University)
저널정보
한국컴퓨터정보학회 한국컴퓨터정보학회논문지 한국컴퓨터정보학회 논문지 제22권 제7호(통권 제160호)
발행연도
2017.7
수록면
75 - 82 (8page)

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초록· 키워드

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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.

목차

Abstract
Ⅰ. Introduction
Ⅱ. Theoretical background
Ⅲ. Method
Ⅳ. Result
Ⅴ. Concluding Remarks
Reference

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UCI(KEPA) : I410-ECN-0101-2018-004-001162855