Transactions of Society of Automotive Engineers of Japan
Online ISSN : 1883-0811
Print ISSN : 0287-8321
ISSN-L : 0287-8321
Technical Paper
Driver Emotion Estimation via Convolutional Neural Network with ECG
Shigeki ShimizuTetsuhiro ItoYingjie YinShun ArakawaOsamu SawadaIsao Aoyagi
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2019 Volume 50 Issue 2 Pages 505-510

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Abstract
How to estimate the driver's emotion is an important topic and has attracted much attention. Some basic research results have been reported in literature, but many problems are still unsolved especially towards the practical application. In this paper, we propose a new method to estimate the driver’s emotion in positive, negative and neutral state via deep learning by driver’s biological signals, where the ECG(ElectroCardioGram) data sequence is changed to an image. The estimating accuracy is up to 90% by our initial experiment results. Furthermore, we show the features of emotion with the Grad-CAM method and find that they appear in T and U wave of ECG instead of R wave, which means a new explanation.
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© 2019 Society of Automotive Engineers of Japan, Inc.
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