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BEC-1D: Biosignal-Based Emotions Classification with 1D ConvNet

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Advances in Soft Computing (MICAI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14392))

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Abstract

Biomedical signals can be used to diagnose several affections of the human body. Nonetheless, they can also be used to describe a more general behavior of specific organs and how they respond according to the feelings and emotions of a person. Therefore, the YAAD dataset, which contains electrocardiogram (ECG) and Galvanic Skin Response (GSR) signals, is used in order to detect and classify seven different emotions from 25 different subjects. Stimulus is provoked to the subjects by exposing them to watch a collection of different videos that evoke emotions, such as anger, happiness, sadness, among others. Two different subsets are used in this research, a single-modal and multi-modal signals. In this work, we propose a series of preprocessing techniques to clean and resample the original signals, then a simple 1-dimensional convolutional neural network is implemented to perform the classification task. Moreover, two different types of validation methods were used to validate our results. We have achieved an accuracy over 95% for both validation methods on the multi-modal subset and an accuracy over 85% for the single-modal subset.

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Acknowledgements

The authors gratefully acknowledge the Instituto Politécnico Nacional (Secretaría Académica, Comisión de Operación y Fomento de Actividades Académicas, Secretaría de Investigación y Posgrado, Centro de Investigación en Computación) and the Consejo Nacional de Humanidades Ciencias y Tecnologías (CONAHCYT) for their economic support to develop this work.

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Authors and Affiliations

  1. Centro de Investigación en Computación, Instituto Politécnico Nacional, 07738, Mexico City, Mexico

    Juan Eduardo Luján-García, Marco A. Cardoso-Moreno, Cornelio Yáñez-Márquez & Hiram Calvo

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  1. Juan Eduardo Luján-García
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  2. Marco A. Cardoso-Moreno
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  3. Cornelio Yáñez-Márquez
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  4. Hiram Calvo
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Corresponding author

Correspondence to Juan Eduardo Luján-García .

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Editors and Affiliations

  1. Center for Computing Research, Instituto Politécnico Nacional, Ciudad de México, Distrito Federal, Mexico

    Hiram Calvo

  2. Facultad de Ingeniería, Universidad Panamericana, Ciudad de México, Mexico

    Lourdes Martínez-Villaseñor

  3. Facultad de Ingeniería, Universidad Panamericana, Ciudad de México, Mexico

    Hiram Ponce

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Luján-García, J.E., Cardoso-Moreno, M.A., Yáñez-Márquez, C., Calvo, H. (2024). BEC-1D: Biosignal-Based Emotions Classification with 1D ConvNet. In: Calvo, H., Martínez-Villaseñor, L., Ponce, H. (eds) Advances in Soft Computing. MICAI 2023. Lecture Notes in Computer Science(), vol 14392. Springer, Cham. https://doi.org/10.1007/978-3-031-47640-2_16

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  • DOI: https://doi.org/10.1007/978-3-031-47640-2_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47639-6

  • Online ISBN: 978-3-031-47640-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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