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ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal

Emotions play an important role in human cognition, perception, decision making, and interaction. This paper presents a six-layer biologically inspired feedforward neural network to discriminate human emotions from EEG. The neural network comprises a shift register memory after spectral filtering fo...

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Main Authors: Khosrowabadi, Reza, Quek, Chai, Ang, Kai Keng, Abdul Rahman, Abdul Wahab
Format: Article
Language:English
English
Published: IEEE Computational Intelligence Society 2014
Subjects:
QA75 Electronic computers. Computer science
TL500 Aeronautics
Online Access:http://irep.iium.edu.my/36713/1/36713.pdf
http://irep.iium.edu.my/36713/3/36713_A%20biologically%20inspired%20feedforward%20neural_Scopus.pdf
http://irep.iium.edu.my/36713/
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spelling my.iium.irep.36713 http://irep.iium.edu.my/36713/ ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal Khosrowabadi, Reza Quek, Chai Ang, Kai Keng Abdul Rahman, Abdul Wahab QA75 Electronic computers. Computer science TL500 Aeronautics Emotions play an important role in human cognition, perception, decision making, and interaction. This paper presents a six-layer biologically inspired feedforward neural network to discriminate human emotions from EEG. The neural network comprises a shift register memory after spectral filtering for the input layer, and the estimation of coherence between each pair of input signals for the hidden layer. EEG data are collected from 57 healthy participants from eight locations while subjected to audio-visual stimuli. Discrimination of emotions from EEG is investigated based on valence and arousal levels. The accuracy of the proposed neural network is compared with various feature extraction methods and feedforward learning algorithms. The results showed that the highest accuracy is achieved when using the proposed neural network with a type of radial basis function. IEEE Computational Intelligence Society 2014-03 Article PeerReviewed application/pdf en http://irep.iium.edu.my/36713/1/36713.pdf application/pdf en http://irep.iium.edu.my/36713/3/36713_A%20biologically%20inspired%20feedforward%20neural_Scopus.pdf Khosrowabadi, Reza and Quek, Chai and Ang, Kai Keng and Abdul Rahman, Abdul Wahab (2014) ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal. IEEE Transactions on Neural Networks and Learning Systems, 25 (3). pp. 609-620. ISSN 2162-237X 10.1109/TNNLS.2013.2280271
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
TL500 Aeronautics
spellingShingle QA75 Electronic computers. Computer science
TL500 Aeronautics
Khosrowabadi, Reza
Quek, Chai
Ang, Kai Keng
Abdul Rahman, Abdul Wahab
ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal
description Emotions play an important role in human cognition, perception, decision making, and interaction. This paper presents a six-layer biologically inspired feedforward neural network to discriminate human emotions from EEG. The neural network comprises a shift register memory after spectral filtering for the input layer, and the estimation of coherence between each pair of input signals for the hidden layer. EEG data are collected from 57 healthy participants from eight locations while subjected to audio-visual stimuli. Discrimination of emotions from EEG is investigated based on valence and arousal levels. The accuracy of the proposed neural network is compared with various feature extraction methods and feedforward learning algorithms. The results showed that the highest accuracy is achieved when using the proposed neural network with a type of radial basis function.
format Article
author Khosrowabadi, Reza
Quek, Chai
Ang, Kai Keng
Abdul Rahman, Abdul Wahab
author_facet Khosrowabadi, Reza
Quek, Chai
Ang, Kai Keng
Abdul Rahman, Abdul Wahab
author_sort Khosrowabadi, Reza
title ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal
title_short ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal
title_full ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal
title_fullStr ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal
title_full_unstemmed ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal
title_sort ernn: a biologically inspired feedforward neural network to discriminate emotion from eeg signal
publisher IEEE Computational Intelligence Society
publishDate 2014
url http://irep.iium.edu.my/36713/1/36713.pdf
http://irep.iium.edu.my/36713/3/36713_A%20biologically%20inspired%20feedforward%20neural_Scopus.pdf
http://irep.iium.edu.my/36713/
_version_ 1643616614230261760
score 13.211869

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