Title: Design of Intelligent EEG System for Human Emotion Recognition with Convolutional Neural Network
Authors: Wang, Kai-Yen
Ho, Yun-Lung
Huang, Yu-De
Fang, Wai-Chi
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
Keywords: Emotion Recognition;Convolutional Neural Network;Deep Learning;Hardware Machine Learning;Real-time EEG System;Affective Computing
Issue Date: 1-Jan-2019
Abstract: 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%.
URI: http://hdl.handle.net/11536/153280
ISBN: 978-1-5386-7884-8
Journal: 2019 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2019)
Begin Page: 142
End Page: 145
Appears in Collections:Conferences Paper