Browse > Article
http://dx.doi.org/10.5370/KIEE.2014.63.5.696

Comparison of EEG Feature Vector for Emotion Classification according to Music Listening  

Lee, So-Min (Dept. of Media Software, Sangmyung University)
Byun, Sung-Woo (Dept. of Media Software, Sangmyung University)
Lee, Seok-Pil (Dept. of Media Software, Sangmyung University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.63, no.5, 2014 , pp. 696-702 More about this Journal
Abstract
Recently, researches on analyzing relationship between the state of emotion and musical stimuli using EEG are increasing. A selection of feature vectors is very important for the performance of EEG pattern classifiers. This paper proposes a comparison of EEG feature vectors for emotion classification according to music listening. For this, we extract some feature vectors like DAMV, IAV, LPC, LPCC from EEG signals in each class related to music listening and compare a separability of the extracted feature vectors using Bhattacharyya distance. So more effective feature vectors are recommended for emotion classification according to music listening.
Keywords
Bhattacharrya distance; EEG; DAMV; IAV; LPC; LPCC; Emotion classification;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Robert Horlings, Dragos Datcu, Leon J. M. Rothkrantz, "Emotion recognition using brain activity", CompSysTech International Conference on Computer Systems and Technologies, Article No. 6, Sept 2008.
2 D. O. Bos. (2006). EEG-based emotion recognition: The influence of visual and auditory stimuli. [Online]. Available: http://hmi.ewi.utwente.nl/verslagen/capita-selecta/CS-Oude_Bos-Danny.pdf.
3 Bernard Harris, Isak Gath, "On time delay estimation of epileptic EEG", IEEE Trans.Biomedical Eng. Vol. 41, No. 9, September 1994.
4 C.J. Stam, B. Jellesa, H.A.M. Achtereektea, S.A.R.B. Romboutsa, J.P.J. Slaetsb, R.W.M. Keunena, "Investigation of EEG non-linearity in dementia and Parkinson's disease", Electroencephalography and Clinical Neurophysiology, Volume 95, Issue 5, pp. 309-317, November 1995.   DOI   ScienceOn
5 Petrantonakis, P.C, Hadjileontiadis, L.J, "Emotion Recognition From EEG Using Higher Order Crossings", IEEE Transactions on Information Technology in Biomedicine, Volume 14, Issue 2, Pages 186-197, March 2010.   DOI   ScienceOn
6 Kwang-Eun Ko, Hyun-Chang Yang, Kwee-Bo Sim, "Emotion recognition using EEG signals with relative power values and Bayesian network", International Journal of Control, Automation and Systems, Volume 7, Issue 5, pp. 865-870, October 2009.   DOI   ScienceOn
7 Vijayalakshmi, K, Sridhar, S, Khanwani, P. "Estimation of effects of alpha music on EEG components by time and frequency domain analysis", IEEE 2010 International Conference on Computer and Communication Engineering (ICCCE), pp. 1-5, May 2010.
8 Varotto G, Fazio, P, Sebastiano, D.R, Avanzini, G, Franceschetti, S, Panzica, F. "Music and emotion: An EEG connectivity study in patients with disorders of consciousness", IEEE 2012 Annual International Conference on Engineering in Medicine and Biology Society (EMBC), pp. 5206-5209, August 2012.
9 J.Kim, Andre, E, "Emotion recognition based on physiological changes in music listening", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30, No.12, pp 2067-2083, 2008.   DOI   ScienceOn
10 Sung-Woo Byun, So-min Lee, Seok-Pil Lee, "A Selection of Optimal EEG Channel for Emotion Analysis According to Music Listening using Stochastic Variables", KIEE, Vol. 62, No. 11, pp 1598-1603, 2013.   과학기술학회마을   DOI   ScienceOn
11 Seok-Pil Lee, Sang-Hui Park, Jeong-Seop Kim, Ig-Jae Kim "EMG pattern recognition based on evidence accumulation for prosthesis control", Proc Ann Intl Conf IEEE Eng Med Biol 4, pp 1481-1483, 1996.
12 Min Han, Leilei Sun "EEG signal classification for epilepsy diagnosis based on AR model and RVM", IEEE 2010 International Conference on Intelligent Control and Information Processing (ICICIP), pp.134-139, Aug 2010.
13 Dror Lederman, Joseph Tabrikian, "Classification of multichannel EEG patterns using parallel hidden Markov models", Medical & Biological Engineering & Computing, Vol 50, Issue 4, pp 319-328, April 2012.   DOI   ScienceOn
14 Eun_Young Kim, "The effect of musical stimulus on EEG spectra of listeners", Korean Music Therapy Association, Vol. 7, No. 1호, pp.1-18, 2005.
15 Padmasai, Y외 3인, "Linear Prediction Modelling for the Analysis of the Epileptic EEG", IEEE-Advances in Computer Engineering (ACE), 2010 International Conference on, pp.6-9, June 2010.
16 S.Koelstra, Muhl, C, Soleymani, M, Jong-Seok Lee, Yazdani, A, Ebrahimi, T, Pun, T, Nijholt, A, Patras, I. "DEAP: A Database for Emotion Analysis using Physiological Signals", IEEE Transaction on Affective Computing-Special Issue on Naturalistic Affect Resources for System Building and Evaluation, vol.3, no.1, pp.18-31, March 2012.
17 Hyungseob Han, Uipil Chong "Electroencephalogram-based Driver Drowsiness Detection System Using AR Coefficients and SVM", Journal of Korean institute of intelligent systems Vol. 22, No. 6, pp.768-773, 2012.   DOI   ScienceOn