Artificial Neural Network-based Emotion Classification Using Physiological Signal

被引：0
|
作者：
Lin, Shu-Yen [1 ]
Liao, Guan-Hao [1 ]
机构：
[1] Yuan Ze Univ, Dept Elect Engn, Jhongli 32003, Taiwan
来源：
2020 6TH INTERNATIONAL CONFERENCE ON APPLIED SYSTEM INNOVATION (ICASI) | 2020年
关键词：
PPG; SVM; Neural Network; Emotion Classification; PHOTOPLETHYSMOGRAPHY;
D O I：
10.1109/ICASI49664.2020.9426328
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this work, we propose an artificial neural network based emotion classification (ANN-EC) with two opposite emotions, happiness and sadness. Compared with the support vector machine based emotion classification (SVM-EC), ANN-EC performs more flexible in classification. Also, ANN-EC shows higher accuracy than SVM-EC. ANN-EC with multiple features reaches 96.25% accuracy and it performs better than just using asingle feature.
引用
收藏
页码：27 / 29
页数：3
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