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Nonlinear Methodologies Applied to Automatic Recognition of Emotions: An EEG Review

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Ubiquitous Computing and Ambient Intelligence (UCAmI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10586))

Abstract

Development of algorithms for automatic detection of emotions is essential to improve affective skills of human-computer interfaces. In the literature, a wide variety of linear methodologies have been applied with the aim of defining the brain’s performance under different emotional states. Nevertheless, recent findings have demonstrated the nonlinear and dynamic behavior of the brain. Thus, the use of nonlinear analysis techniques has notably increased, reporting promising results with respect to traditional linear methods. In this sense, this work presents a review of the latest advances in the field, exploring the main nonlinear metrics used for emotion recognition from EEG recordings.

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Acknowledgments

This work was partially supported by Spanish Ministerio de Economía, Industria y Competitividad, Agencia Estatal de Investigación (AEI)/European Regional Development Fund under Vi-SMARt (TIN2016-79100-R), HA-SYMBIOSIS (TIN2015-72931-EXP) and EmoBioFeedback (DPI2016-80894-R) grants. Beatriz García-Martínez holds the FPU16/03740 scholarship from Spanish Ministerio de Educación, Cultura y Deporte.

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Authors and Affiliations

  1. Instituto de Tecnologías Audiovisuales, Universidad de Castilla-La Mancha, 16071, Cuenca, Spain

    Beatriz García-Martínez, Arturo Martínez-Rodrigo & Raúl Alcaraz

  2. Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, 02071, Albacete, Spain

    Antonio Fernández-Caballero & Pascual González

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  1. Beatriz García-Martínez
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  2. Arturo Martínez-Rodrigo
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Correspondence to Arturo Martínez-Rodrigo .

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  1. University of Santiago Chile, Santiago, Chile

    Sergio F. Ochoa

  2. Villanova University, Villanova, Pennsylvania, USA

    Pritpal Singh

  3. University of Castilla La Mancha, Ciudad Real, Spain

    José Bravo

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García-Martínez, B., Martínez-Rodrigo, A., Alcaraz, R., Fernández-Caballero, A., González, P. (2017). Nonlinear Methodologies Applied to Automatic Recognition of Emotions: An EEG Review. In: Ochoa, S., Singh, P., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2017. Lecture Notes in Computer Science(), vol 10586. Springer, Cham. https://doi.org/10.1007/978-3-319-67585-5_73

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