Browse > Article
http://dx.doi.org/10.5370/KIEE.2013.62.11.1598

A Selection of Optimal EEG Channel for Emotion Analysis According to Music Listening using Stochastic Variables  

Byun, Sung-Woo (Dept. of Digital Media Technology, Sangmyung University)
Lee, So-Min (Dept. of Digital Media Technology, Sangmyung University)
Lee, Seok-Pil (Dept. of Digital Media Technology, Sangmyung University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.62, no.11, 2013 , pp. 1598-1603 More about this Journal
Abstract
Recently, researches on analyzing relationship between the state of emotion and musical stimuli are increasing. In many previous works, data sets from all extracted channels are used for pattern classification. But these methods have problems in computational complexity and inaccuracy. This paper proposes a selection of optimal EEG channel to reflect the state of emotion efficiently according to music listening by analyzing stochastic feature vectors. This makes EEG pattern classification relatively simple by reducing the number of dataset to process.
Keywords
EEG; Music; Emotion analysis; LPC; Variance;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Chiu, H.W, Lin, L.S, Kuo, M.C, Chiang, H.S, Hsu, C.Y "Using heart rate variability analysis to assess the effect of music therapy on anxiety reduction of patients", IEEE Conference on Computers in Cardiology, pp.469-472, Sept 2003.
2 Yuan-Pin Lin, Chi-Hong Wang, Tzyy-Ping Jung, Tien-Lin Wu, Shyh-Kang Jeng, Jeng-Ren Duann, Jyh-Horng Chen "EEG-Based Emotion Recognition in Music Listening.", IEEE Transactions on Biomedical Engineering, Volume:57, Issue:7, pp.1798-1806, May 2010.   DOI   ScienceOn
3 Dongki Kang, Honghwan Kim, Dongjun Kim, Byungchae Lee, Hanwoo Ko "Research on classification of emotion using multi-channel EEG", KIEE Conference, pp.2815-2817, 2001.
4 Hyekyung Lee, Seungjin Choi "PCA+HMM+SVM for EEG pattern classification", IEEE Seventh International Symposium on Signal Processing and Its Applications, vol.1, pp.541-544, July 2003.
5 del R Millan, J, Mourino, J, Franze, M, Cincotti, F, Varsta, M, Heikkonen, J, Babiloni, F. "A local neural classifier for the recognition of EEG patterns associated to mental tasks", IEEE Transactions on Neural Networks, vol. 13, no. 3, pp.678-686, May 2002.   DOI   ScienceOn
6 Ruey S.Huang, Kuo, C.J, Ling-Ling Tsai, Chen, O.T.-C. "EEG pattern recognition-arousal states detection and classification.", IEEE International Conference on Neural Networks, 1996, Volume:2, pp.641-646, Jun 1996.
7 Kai Xu, Yan Wu, "Motor imagery EEG Recognition based on Biomimetic Pattern Recognition", IEEE 2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI), Volume:3, pp.955-959, 2010.
8 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.
9 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.
10 Tseng, Kevin C, Lin, Bor-Shyh, Han, Chang-Mu, Wang, Psi-Sh,i "Emotion recognition of EEG underlying favourite music by support vector machine", IEEE 2013 International Conference on Orange Technologies (ICOT), pp.155-158 ,March 2013.
11 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
12 Athanasios Papoulis, "Probability, Random Variables, and Stochastic Processes. third Edition" McGRAW-HILL, Inc, pp.106-109, Jan 1991.
13 Kyibo Shim, Seungmin Park, Kwangeun Ko, Joonyup Kim "A method for optimal EEG channel selection based on BPSO with channel impact factor", Journal of KIIS, vol. 22, no. 6, pp.774-779, 2012.
14 Padmasai, Y, SubbaRao, K, Malini, V, Rao, C.R. "Linear Prediction Modelling for the Analysis of the Epileptic EEG", IEEE 2010 International Conference on Advances in Computer Engineering (ACE), pp.6-9, June 2010.
15 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.
16 Lias, S, Murat, Z.H, Sulaiman, N, Taib, M.N "IQ Index using Alpha-Beta correlation of EEG power spectrum density (PSD)", IEEE 2010 Symposium on Industrial Electronics & Applications (ISIEA), pp.612-616, Oct. 2010.
17 Eunyoung Kim, "The effects of musical stimulus on EEG spectra of listeners", Journal of KMTA, vol. 7, no. 1, pp.1-18, 2005.
18 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