Short-time-span EEG-based personalized emotion recognition with deep convolutional neural network

Kit Hwa Cheah, Humaira Nisar, Vooi Voon Yap, Chen Yi Lee

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

Abstract

Emotion recognition can be useful in various applications such as in neurofeedback training for functional enhancement. A practically realizable emotion recognition system should rely on as little physiological signals/modalities as possible. Also, emotion-related neurological activities may be vastly different from person to person. Hence, this paper presents the single-modal EEG-based personalized emotion recognition convolutional neural network (CNN) models working on the DEAP dataset. The valence and arousal level classification performance of our presented CNN classifiers have surpassed the other emotion classifiers working on the DEAP dataset based on our scope of literature reviewed. The models, which are deep CNN, rely on only plain EEG data and require no pre-extracted EEG features. The design and application of the CNN models is aimed at possible future work of identification of new emotion-related EEG features, relying on the automated feature extraction capability of the CNN. The two CNN models presented have achieved the 3-class valence classification test accuracy of 97.59% and 98.75% respectively, and the 3-class arousal classification test accuracy of 98.48% and 97.58%.

Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages78-83
Number of pages6
ISBN (Electronic)9781728133775
DOIs
StatePublished - Sep 2019
Event2019 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2019 - Kuala Lumpur, Malaysia
Duration: 17 Sep 201919 Sep 2019

Publication series

NameProceedings of the 2019 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2019

Conference

Conference2019 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2019
CountryMalaysia
CityKuala Lumpur
Period17/09/1919/09/19

Keywords

  • arousal
  • DEAP
  • dilated convolution
  • EEG
  • Emotion classification
  • neural network
  • transferred learning
  • valence

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