TY  - JOUR
PY  - 2019//
TI  - Driver emotion estimation via convolutional neural network with ECG
JO  - Transactions of Society of Automotive Engineers of Japan
A1  - Shimizu, Shigeki
A1  - Ito, Tetsuhiro
A1  - Yin, Yingjie
A1  - Arakawa, Shun
A1  - Sawada, Osamu
A1  - Aoyagi, Isao
SP  - 505
EP  - 510
VL  - 50
IS  - 2
N2  - 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.<p /> <p>Language: ja</p>
LA  - ja
SN  - 0287-8321
UR  - http://dx.doi.org/10.11351/jsaeronbun.50.505
ID  - ref1
ER  -