Abstract
Emotions are very essential for our day-to-day activities such as communication, decision-making and learning. Electroencephalography (EEG) is a non-invasive method to record electrical activity of the brain. To make Human–Machine Interaction (HMI) more natural, human emotion recognition is important. Over the past decade, various signal processing methods are used for analysing EEG-based emotion recognition (ER). This paper proposes a novel technique for ER using Gray-Level Co-occurrence Matrix (GLCM)-based features. The features are validated on benchmark DEAP database upto four emotions and classified using K-nearest neighbor (K-NN) classifier.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rafael A. Calvoand., Sidney DMello.: Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications. IEEE Transactions on Affective Computing. vol. 1, no. 1, 18–37 (2010).
R. M. Haralick., S. Shanmugam., I. Dinstein.: Textural features for image classification. IEEE Transactions on Systems, Man and Cybernetics. SMC., Vol. 3, 610–621 (1973).
J. F. Haddon., J. F. Boyce.: Co-occurrence matrices for image analysis. IEEE Electronics & Communication Engineering Journal. Vol. 5, 71–83 (1993).
C. W. D. de Almeida., R.M. C. R. de Souza., A. L. B. Candeias.: Texture classification based on co-occurrence matrix and self organizing map. IEEE International conference on Systems Man & Cybernetics. University of Pernambuco Recife. 2487–2491 (2010).
A.A. Mohammad., B. Khosrow, J. R. Burk., E. A. Lucas., M. Manry.: A New Method to Detect Obstructive Sleep Apnea Using Fuzzy Classification of Time-Frequency Plots of the Heart Rate Variability. 28th Annual International Conference of the IEEE in Engineering in Medicine and Biology Society, 2006. EMBS ’06. 6493–6496 (2006).
M. Saad., M. Nor, F. Bustami., and R. Ngadiran.: Classification of Heart Abnormalities Using Artificial Neural Network. Journal of Applied Sciences, vol. 7, 820–825(2007).
Mahfuzah Mustafa., Mohd Nasir Taib., Zunairah Hj. Murat., Noor Hayatee Abdul Hamid.: GLCM Texture Classification for EEG Spectrogram Image. IEEE EMBS Conference on Biomedical Engineering & Sciences (IECBES 2010), Kuala Lumpur, Malaysia, 426–429 (2010).
Mahfuzah Mustafa., Mohd Nasir Taib., Sahrim Lias., Zunairah Hj. Murat, Norizam S.: EEG Spectrogram Classification Employing ANN for IQ Application. International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE 2013), Konya, Turkey, 199–203 (2013).
F. Florea, E. Barbu., A. Rogozan., and A. Bensrhair.: Using texture based symbolic features for medical image representation. 18th International Conference on Pattern Recognition, 2006. ICPR 2006, 946–949 (2006).
Sander Koelstra., Christian Muhl., Mohammad Soleymani., Jong-Seok Lee., Ashkan Yazdani., Touradj Ebrahimi., Thierry Pun., Anton Nijholt., Ioannis Patras.: DEAP: A Database for Emotion Analysis using Physiological Signals. IEEE Transactions on Affective Computing. vol. 3, no. 1, (2012).
S. Koelstra et al., 2012, DEAP Dataset available at http://www.eecs.qmul.ac.uk/mmv/datasets/deap/
J.A. Russell.: A Circumplex Model of Affect. J. Personality and Social Psychology, vol. 39, no. 6, 1161–1178 (1980).
R. O. Duda., P. E. Hart., D. G. Stork.: Pattern Classification. 2nd ed., Wiley-Interscience (2001).
T. F. Bastos-Filho., A. Ferreira, A. C. Atencio., S. Arjunan., D. Kumar.: Evaluation of feature extraction techniques in emotional state recognition. 4th Int. Conf. Intell. Hum. Comput. Interact. Adv. Technol. Humanit. IHCI 2012, (2012).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media Singapore
About this paper
Cite this paper
Jadhav, N., Manthalkar, R., Joshi, Y. (2017). Electroencephalography-Based Emotion Recognition Using Gray-Level Co-occurrence Matrix Features. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-10-2104-6_30
Download citation
DOI: https://doi.org/10.1007/978-981-10-2104-6_30
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-2103-9
Online ISBN: 978-981-10-2104-6
eBook Packages: EngineeringEngineering (R0)