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Classifying the Deceptive and Truthful Responses Through Ocular Measures in an Interview Process

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New Perspectives in Software Engineering (CIMPS 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1416))

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Abstract

Deceptive responses into an interview need more cognitive load than truthful ones. A high cognitive load is presented on working memory in lying. Cognitive load is widely measured in eye-tracking studies with ocular data as pupil dilations, blinks, saccades, and fixations. Only a few studies explore the cognitive load of memory tasks during lying conditions through ocular measures. In addition to this, there is no integration of these measures into a software model for practical implications over interviews or interrogatories, i.e., a classifier of deceptive and truthful responses. Cognitive load measures associated with the lie and truth were studied in teenagers such as the entropy of eye-fixations, saccadic peak velocity, blink frequency, and pupil size change, selecting the features with significant differences and training the Support Vector Machine (SVM) and Quadratic Discriminant Analysis (QDA) models. SVM presented 80% of accuracy and QDA the 40% for the classification of deceptive and truthful responses.

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Authors and Affiliations

  1. Computer Science Department, Mathematics Research Center (CIMAT), Quantum: Knowledge City, Zacatecas, Mexico

    Hugo Mitre-Hernandez

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  1. Hugo Mitre-Hernandez
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Correspondence to Hugo Mitre-Hernandez .

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Editors and Affiliations

  1. Centro de Investigación en Matemáticas A.C., Unidad Zacatecas, Zacatecas, Mexico

    Jezreel Mejia

  2. Centro de Investigación en Matemáticas A.C., Unidad Zacatecas, Zacatecas, Mexico

    Mirna Muñoz

  3. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  4. Centro Universitario de los Valles, University of Guadalajara, Jalisco, Mexico

    Himer Avila-George

  5. Universidad Tecnológica de Torreón, Coahuila, Mexico

    Gloria Monica Martínez-Aguilar

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Mitre-Hernandez, H. (2022). Classifying the Deceptive and Truthful Responses Through Ocular Measures in an Interview Process. In: Mejia, J., Muñoz, M., Rocha, Á., Avila-George, H., Martínez-Aguilar, G.M. (eds) New Perspectives in Software Engineering. CIMPS 2021. Advances in Intelligent Systems and Computing, vol 1416. Springer, Cham. https://doi.org/10.1007/978-3-030-89909-7_19

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