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

QR Code

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...

Full description

Bibliographic Details
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/ http://irep.iium.edu.my/36713/1/36713.pdf http://irep.iium.edu.my/36713/3/36713_A%20biologically%20inspired%20feedforward%20neural_Scopus.pdf

Similar Items

Classification of EEG correlates on emotion using features from Gaussian mixtures of EEG spectrogram
by: Khosrowabadi, Reza, et al.
Published: (2011)

EEG-based emotion recognition using self-organizing map for boundary detection
by: Khosrowabadi, Reza, et al.
Published: (2010)

EEG signals for emotion recognition
by: Abdul Rahman, Abdul Wahab, et al.
Published: (2010)

Affective computation on EEG correlates of emotion from musical and vocal stimuli
by: Khosrowabadi, Reza, et al.
Published: (2009)

Emotion detection using physiological signals EEG & ECG
by: AlzeerAlhouseini, Amjad M.R., et al.
Published: (2016)

CMAC-based computational model of affects (CCMA) for profiling emotion from EEG signals
by: Yaacob, Hamwira Sakti, et al.
Published: (2014)

EEG emotion recognition based on the dimensional models of emotions
by: Othman, Marini, et al.
Published: (2013)

Speech emotion recognition using deep feedforward neural network
by: Alghifari, Muhammad Fahreza, et al.
Published: (2018)

EEG emotion recognition using features of Mel Frequency Cepstral Coefficients
by: Othman, Marini, et al.
Published: (2011)

Emotion recognition using EEG signals
by: Abdul Aziz, Normaziah, et al.
Published: (2011)

EEG emotion recognition system
by: Ma, Li Ya, et al.
Published: (2009)

Biologically-Inspired Modeling of Filtering Noise in Signal Sound
by: Hammuzamer , Irwan, et al.
Published: (2009)

Biologically-Inspired Abstraction Model to Analyze Sound Signal
by: Hammuzamer Irwan , Hamzah, et al.
Published: (2008)

Classification of multichannel EEG signal by linear discriminant analysis
by: Hasan, Mohammad Rubaiyat, et al.
Published: (2015)

Classification of multichannel EEG signal by linear discriminant analysis
by: Hasan, Mohammad Rubaiyat, et al.
Published: (2015)

Frequency modulation in EEG signals
by: Vijayakumar, V., et al.
Published: (2006)

A Proposed Model of Biologically-Inspired Sound Signal Analyzer
by: Hammuzamer , Irwan, et al.
Published: (2009)

A Proposed Biologically-Inspired Model to Analyze Signal Sound
by: Hammuzamer Irwan , Hamzah, et al.
Published: (2009)

Epilepsy detection using EEG signals
by: Amer, Salam, et al.
Published: (2018)

A New Abstraction Model for Biologically- Inspired Sound Signal Analyzer
by: Hammuzamer Irwan , Hamzah, et al.
Published: (2009)

Statistical approach for a complex emotion recognition based on EEG features
by: Dwi Handayani, Dini Oktarina, et al.
Published: (2016)

Investment decisions based on EEG emotion recognition
by: Mat Razi, Nurul Izzati, et al.
Published: (2017)

A Proposed Application Model for a Biologically-Inspired Sound Signal Analyzer
by: Hammuzamer, Irwan, et al.
Published: (2009)

A Proposed Application Model for a Biologically-Inspired Sound Signal Analyzer
by: Hammuzamer Irwan, Hamzah, et al.
Published: (2009)

Biologically Inspired Signal Noise Elimination Using Human Ear Model with Concurrent Algorithm
by: Hammuzamer Irwan, Hamzah, et al.
Published: (2008)

Emotion detection from brain signals based on musical and visual stimuli
by: Othman, Marini, et al.
Published: (2011)

Dynamic unsupervised feedforward neural network clustering / Roya Asadi
by: Roya, Asadi
Published: (2016)

The dynamic emotion recognition system based on functional connectivity of brain regions
by: Khosrowabadi , Reza, et al.
Published: (2010)

Dynamic tunneling based regularization in feedforward neural networks
by: Singh, Y.P., et al.
Published: (2001)

Cultural dependency analysis for understanding speech emotion
by: Kamaruddin, Norhaslinda, et al.
Published: (2012)

Detection of eye movements based on EEG signals and the SAX algorithm
by: Shanmuga, P. M. M., et al.
Published: (2018)

Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals
by: Badaruddin, Muhammad, et al.
Published: (2018)

A study on the effects of EEG and ECG signals while listening to Qur'an recitation
by: Alshaikhli, Imad Fakhri Taha, et al.
Published: (2014)

Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm
by: Sulaiman, Suriani, et al.
Published: (2015)

Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm
by: Sulaiman, Suriani, et al.
Published: (2015)

An Adaptive Error Modeling Scheme for the Lossless Compression of EEG Signals
by: Sriraam, N., et al.
Published: (2008)

Novel face recognition approach using bit-level information and dummy blank images in feedforward neural network
by: Boon, David Liang Bong, et al.
Published: (2009)

Understanding students’ emotion while solving mathematical questions using EEG signals
by: Abdul Aziz, Normaziah, et al.
Published: (2011)

Classification of EEG signals using MLP based on categorical and dimensional perceptions of emotions.
by: Yaacob, Hamwira Sakti, et al.
Published: (2013)

Epilepsy detection from EEG signals using artificial neural network
by: Sallam, Amer A., et al.
Published: (2019)