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Converging Clinical and Engineering Research on Neurorehabilitation II pp 783–787Cite as

A Stress Classification System Based on Arousal Analysis of the Nervous System

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Part of the Biosystems & Biorobotics book series (BIOSYSROB,volume 15)

Abstract

Detection of an increment in stress levels is a step towards improving the quality of people’s lives, especially in the case of people with intellectual disabilities, as they have fewer resources to deal with this situation. This paper presents a biophysical stress classification system that is able to classify the detected stress situations at three intensity levels: low, medium and high. Furthermore, the system distinguishes between continued stress and a momentary alert depending on the subject’s arousal. The system uses two non-invasive physiological signals for the classification: the galvanic skin response and the heart rate variability. The experiment shows that the proposed system is able to detect and classify the different stress states achieving an accuracy of 97.5 % with a 0.9 % FN rate.

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  • DOI: 10.1007/978-3-319-46669-9_128
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Acknowledgments

This work described in this paper was partially supported by the University of the Basque Country (BAILab, grant UFI11/45); by the Department of Education, Universities and Research (grant IT-395-10); and by the Ministry of Economy and Competitiveness of the Spanish Government and by the European Regional Development Fund—ERDF (eGovernAbility, grant TIN2014-52665-C2-1-R).

Author information

Authors and Affiliations

  1. Computer Architecture and Technology Department (UPV/EHU), Donostia, Spain

    J. Abascal, A. Arruti, J. I. Martín & J. Muguerza

  2. System Engineering and Automation Department (UPV/EHU), Bilbao, Spain

    R. Martínez & E. Irigoyen

Authors
  1. R. Martínez
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  2. J. Abascal
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  3. A. Arruti
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  4. E. Irigoyen
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  5. J. I. Martín
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  6. J. Muguerza
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Corresponding authors

Correspondence to J. I. Martín or J. Muguerza .

Editor information

Editors and Affiliations

  1. Cajal Institute, Spanish National Research Council Cajal Institute, Madrid, Spain

    Jaime Ibáñez

  2. Cajal Institute, Spanish National Research Council Cajal Institute, Madrid, Spain

    José González-Vargas

  3. Avda. de la Universidad s/n, Universidad Miguel Hernández de Elche Avda. de la Universidad s/n, Elche, Spain

    José María Azorín

  4. Cullen College of Engineering, University of Houston Cullen College of Engineering, Houston, USA

    Metin Akay

  5. Cajal Institute, Spanish National Research Council Cajal Institute, Madrid, Spain

    José Luis Pons

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Martínez, R., Abascal, J., Arruti, A., Irigoyen, E., Martín, J.I., Muguerza, J. (2017). A Stress Classification System Based on Arousal Analysis of the Nervous System. In: Ibáñez, J., González-Vargas, J., Azorín, J., Akay, M., Pons, J. (eds) Converging Clinical and Engineering Research on Neurorehabilitation II. Biosystems & Biorobotics, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-319-46669-9_128

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  • DOI: https://doi.org/10.1007/978-3-319-46669-9_128

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46668-2

  • Online ISBN: 978-3-319-46669-9

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