Design of Intelligent EEG System for Human Emotion Recognition with Convolutional Neural Network

被引：0
|
作者：
Wang, Kai-Yen
Ho, Yun-Lung
Huang, Yu-De
Fang, Wai-Chi [1 ]
机构：
[1] Natl Chiao Tung Univ, Dept Elect Engn, Hsinchu, Taiwan
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2019) | 2019年
关键词：
Emotion Recognition; Convolutional Neural Network; Deep Learning; Hardware Machine Learning; Real-time EEG System; Affective Computing;
D O I：
10.1109/aicas.2019.8771581
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Emotions play a significant role in the field of affective computing and Human-Computer Interfaces(HCI). In this paper, we propose an intelligent human emotion detection system based on EEG features with a multi-channel fused processing. We also proposed an advanced convolutional neural network that was implemented in VLSI hardware design. This hardware design can accelerate both the training and classification processes and meet real-time system requirements for fast emotion detection. The performance of this design was validated using DEAP [1] database with datasets from 32 subjects, the mean classification accuracy achieved is 83.88%.
引用
收藏
页码：142 / 145
页数：4
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