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

Kai Yen Wang, Yun Lung Ho, Yu De Huang, Wai Chi Fang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

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%.

Original languageEnglish
Title of host publicationProceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages142-145
Number of pages4
ISBN (Electronic)9781538678848
DOIs
StatePublished - Mar 2019
Event1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019 - Hsinchu, Taiwan
Duration: 18 Mar 201920 Mar 2019

Publication series

NameProceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019

Conference

Conference1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
CountryTaiwan
CityHsinchu
Period18/03/1920/03/19

Keywords

  • Affective Computing
  • Convolutional Neural Network
  • Deep Learning
  • Emotion Recognition
  • Hardware Machine Learning
  • Real-time EEG System

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