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Recent Advances and Challenges in Nonlinear Characterization of Brain Dynamics for Automatic Recognition of Emotional States

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Natural and Artificial Computation for Biomedicine and Neuroscience (IWINAC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10337))

Abstract

Automatic recognition of emotions is an emerging field, because it plays a key role to improve current affective human-computer interactions. Although for that purpose a variety of linear methods have been applied to the electroencephalographic (EEG) recording, nonlinear analysis has recently revealed novel and more useful insights about the brain behavior under different emotional states. This work briefly reviews the main progresses in this context, also highlighting the main challenges that will have to be mandatory tackled in future.

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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 Funder under HA-SYMBIOSIS (TIN2015-72931-EXP), Vi-SMARt (TIN2016-79100-R) and EmoBioFeedback (DPI2016-80894-R) grants.

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Authors and Affiliations

  1. Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, Cuenca, Spain

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

Authors
  1. Raúl Alcaraz
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  2. Beatriz García-Martínez
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  3. Roberto Zangróniz
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  4. Arturo Martínez-Rodrigo
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Corresponding author

Correspondence to Arturo Martínez-Rodrigo .

Editor information

Editors and Affiliations

  1. Departamento de Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain

    José Manuel Ferrández Vicente

  2. Departamento de Inteligencia Articial, Universidad Nacional de Educación a Distancia, Madrid, Spain

    José Ramón Álvarez-Sánchez

  3. Departamento de Inteligencia Articial, Universidad Nacional de Educación a Distancia, Madrid, Spain

    Félix de la Paz López

  4. Departamento de Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Cartagena, Spain

    Javier Toledo Moreo

  5. The Ohio State University, Columbus, Ohio, USA

    Hojjat Adeli

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Alcaraz, R., García-Martínez, B., Zangróniz, R., Martínez-Rodrigo, A. (2017). Recent Advances and Challenges in Nonlinear Characterization of Brain Dynamics for Automatic Recognition of Emotional States. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) Natural and Artificial Computation for Biomedicine and Neuroscience. IWINAC 2017. Lecture Notes in Computer Science(), vol 10337. Springer, Cham. https://doi.org/10.1007/978-3-319-59740-9_21

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  • DOI: https://doi.org/10.1007/978-3-319-59740-9_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59739-3

  • Online ISBN: 978-3-319-59740-9

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