References

Abhang, P.A. and B.W. Gawali, 2015. Correlation of EEG images and speech signals for emotion analysis. Br. J. Appl. Sci. Technol., 10: 1-13.
CrossRef  |  

Aftanas, L.I., N.V. Reva, S.V. Pavlov, V.V. Korenek and I.V. Brak, 2015. Linkage of brain oscillatory systems with the cognitive (experience and valence) and Physiological (cardiovascular reactivity) components of the emotions. Neurosci. Behav. Physiol., 45: 910-919.
CrossRef  |  Direct Link  |  

Agrafioti, F., 2011. ECG in biometric recognition: Time dependency and application challenges. Ph.D Thesis, University of Toronto, Toronto, Ontario.

Alekseev, A.A., V.L. Rozaliev, Y.A. Orlova and A.V. Zaboleeva-Zotova, 2016. Context-Sensitive Image Analysis for Coloring Nature Images. In: Intelligent Information Technologies for Industry, Abraham A., S. Kovalev, V. Tarassov and V. Snasel (Eds.). Springer, Cham, Switzerland, USA., ISBN:978-3-319-33815-6, pp: 133-141.

Banziger, T., D. Grandjean and K.R. Scherer, 2009. Emotion recognition from expressions in face, voice and body: The Multimodal Emotion Recognition Test (MERT). Emotion, 9: 691-704.
PubMed  |  Direct Link  |  

Blair, R.J.R., J.S. Morris, C.D. Frith, D.I. Perrett and R.J. Dolan, 1999. Dissociable neural responses to facial expressions of sadness and anger. Brain, 122: 883-893.
PubMed  |  Direct Link  |  

Bradley, M.M. and P.J. Lang, 1994. Measuring emotion: The self-assessment manikin and the semantic differential. J. Behav. Ther. Exp. Psychiatry, 25: 49-59.
CrossRef  |  PubMed  |  

Chetouani, M., A. Mahdhaoui and F. Ringeval, 2009. Time-scale feature extractions for emotional speech characterization. Cognit. Comput., 1: 194-201.
PubMed  |  Direct Link  |  

Cowie, E.D., N. Campbell, R. Cowie and P. Roach, 2003. Emotional speech: Towards a new generation of databases. Speech Commun., 40: 33-60.
Direct Link  |  

Crawford, H.J., S.W. Clarke and M. Kitner-Triolo, 1996. Self-generated happy and sad emotions in low and highly hypnotizable persons during waking and hypnosis: Laterality and regional EEG activity differences. Intl. J. Psychophysiology, 24: 239-266.
PubMed  |  Direct Link  |  

Filatova, N.N. and K.V. Sidorov, 2016. Human emotions valency and level change monitoring by means of the EEG and speech signals analysis. Proceedings of the 12th Russian-German Conference on Biomedical Engineering (RGC’16), July 4-7, 2016, Vladimir State University, Suzdal, Russia, pp: 87-91.

Filatova, N.N. and K.V. Sidorov, 2016. Interpretation of the emotion characteristics through the analysis of attractors reconstructed on EEG signals. Fuzzy Syst. Soft Comput., 11: 57-76.
Direct Link  |  

Filatova, N.N., K.V. Sidorov and L.V. Iliasov, 2015. Automated system for analyzing and interpreting nonverbal information. Intl. J. Appl. Eng. Res., 10: 45741-45749.

Filatova, N.N., K.V. Sidorov and S.A. Terekhin, 2015. A software package for interpretation of nonverbal information by analyzing speech patterns or electroencephalogram. Software Syst., 111: 22-27.

Filatova, N.N., K.V. Sidorov, S.A. Terekhin and G.P. Vinogradov, 2016. The System for the Study of the Dynamics of Human Emotional Response using Fuzzy Trends. In: Intelligent Information Technologies for Industry, Springer, Cham, Switzerland, USA., ISBN:978-3-319-33815-6, pp: 175-184.

Flaisch, T., 2007. The neural processing of emotional pictures: Evidence from evoked potentials and functional magnetic resonance imaging. Ph.D Thesis, University of Konstanz, Konstanz, Germany.

Fox, N.A. and R.J. Davidson, 1986. Taste-elicited changes in facial signs of emotion and the asymmetry of brain electrical activity in human newborns. Neuropsychologia, 24: 417-422.
CrossRef  |  PubMed  |  

Fraser, A.M., 1989. Reconstructing attractors from scalar time series: A comparison of singular system and redundancy criteria. Phys. D. Nonlinear Phenom., 34: 391-404.
CrossRef  |  

Gorshkov, V.A. and S.A. Kasatkin, 2008. [Identification of Time Series of Aviation Events by Methods and Algorithms for Nonlinear Dynamics]. Blank Publication, Moscow, Russia, Pages: 208 (In Russia).

Grassberger, P. and I. Procaccia, 1983. Measuring the strangeness of strange attractors. Phys. D., 9: 189-208.

Gratch, J. and S. Marsella, 2005. Evaluating a computational model of emotion. Auton. Agents Multi Agent Syst., 11: 23-43.
Direct Link  |  

Hwang, M., D.H. Jeong, J. Kim, S.K. Song and H. Jung et al., 2013. A term normalization method for efficient knowledge acquisition through text processing. Multimedia Tools Appl., 65: 75-91.
CrossRef  |  

Koelstra, S., 2012. Affective and implicit tagging using facial expressions and electroencephalography. Ph.D Thesis, Queen Mary University of London, London, England.

Lan, Z., O. Sourina, L. Wang and Y. Liu, 2016. Real-time EEG-based emotion monitoring using stable features. Visual Comput., 32: 347-358.
CrossRef  |  Direct Link  |  

Lapshina, T.N., 2007. Psychophysiological diagnosis of human emotions based on EEG indices. Ph.D Thesis, Moscow State University, Moscow, Russia. (In Russia)

Lebedeva, N.N. and E.D. Karimova, 2014. The acoustic characteristics of the speech signal as an indicator of the human functional state. Prog. Physiol., 45: 57-95.
PubMed  |  Direct Link  |  

Lin, J., M. Spraragen and M. Zyda, 2012. Computational models of emotion and cognition. Adv. Cognit. Syst., 2: 59-76.
Direct Link  |  

Liu, Y., O. Sourina and M.K. Nguyen, 2011. Real-Time EEG-Based Emotion Recognition and its Applications. In: Transactions on Computational Science XII, Gavrilova M.L., C.J.K. Tan, A. Sourin and O. Sourina (Eds.). Springer, Berlin, Germany, ISBN:978-3-642-22335-8, pp: 256-277.

Lokannavar, S., P. Lahane, A. Gangurde and P. Chidre, 2015. Emotion recognition using EEG signals. Intl. J. Adv. Res. Comput. Commun. Eng., 4: 54-56.
CrossRef  |  Direct Link  |  

Nikolaevna, F.N. and T.S. Alexeevich, 2015. Bioengineering system for research on human emotional response to external stimuli. Proceedings of the International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON), October 28-30, 2015, IEEE, Novosibirsk, Russia, ISBN:978-1-4673-9109-2, pp: 13-17.

Rabinovich, M.I. and M.K. Muezzinoglu, 2010. Nonlinear dynamics of the brain: Emotion and cognition. Phys. Usp., 53: 357-372.
Direct Link  |  

Rangayyan, R.M., 2015. Biomedical Signal Analysis. 2nd Edn., John Wiley & Sons, Hoboken, New Jersey, USA., ISBN:978-0-470-91139-6, Pages: 720.

Reisenzein, R., E. Hudlicka, M. Dastani, J. Gratch and K. Hindriks et al., 2013. Computational modeling of emotion: Toward improving the inter-and intradisciplinary exchange. IEEE. Trans. Affective Comput., 4: 246-266.
CrossRef  |  Direct Link  |  

Rozaliev, V.L., 2009. Modeling of user’s emotional reactions during speech interaction with an automated system. Ph.D Thesis, Volgograd State Technical University, Volgograd, Russia. (In Russia)

Schroder, M., 2004. Speech and emotion research: An overview of research frameworks and a dimensional approach to emotional speech synthesis. Ph.D Thesis, Saarland University, Saarbrucken, Germany.

Sidorov, K.V. and N.N. Filatova, 2016. The model interpretation of the dynamics emotions by analysis EEG or speech samples. Proceedings of the Conference on Intelligent Systems and IT (IS&IT’16) Vol. 2, September 21-22, 2016, Fizmatlit Publishers, Moscow, Russia, pp: 265-270.

Sidorov, K.V., 2015. A bioengineering system for monitoring human emotions by speech signals and electroencephalograms. Ph.D Thesis, Tver State University, Tver, Russia. (In Russia)

Soloshenko, A.N., Y.A. Orlova, V.L. Rozaliev and A.V. Zaboleeva-Zotova, 2015. Establishing semantic similarity of the cluster documents and extracting key entities in the problem of the semantic analysis of news texts. Mod. Appl. Sci., 9: 246-268.
CrossRef  |  

Starchenko, I.B., J.S. Perervenko, O.S. Borisova and T.V. Momot, 2010. Nonlinear dynamics methods for biomedical applications. Eng. Sci., 110: 42-51.
Direct Link  |  

Takens, F., 1981. Detecting Strange Attractors in Turbulence. In: Dynamical Systems and Turbulence: Lecture Notes in Mathematics, Rand, D.A. and L.S. Young (Eds.). Vol. 899, Springer, Berlin, Heidelberg, pp: 366-381.

Wheeler, R.E., R.J. Davidson and A.J. Tomarken, 1993. Frontal brain asymmetry and emotional reactivity: A biological substrate of affective style. Psychophysiology, 30: 82-89.
CrossRef  |  PubMed  |  Direct Link  |