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<title>Evaluación multimodal de la carga cognitiva en el desempeño  de tareas visomotoras complejas: un estudio sobre el sesgo  implícito en la interacción humano-ia</title>
<creator>Martínez Mora, Sara</creator>
<creator>Morales Balbás, Samuel</creator>
<creator>Sanz Palacios, Teresa</creator>
<creator>Urizarna Sánchez, Alba</creator>
<contributor>Sáiz Manzanares, María Consuelo</contributor>
<contributor>Olivares Gil, Alicia</contributor>
<contributor>Universidad de Burgos. Departamento de Ciencias de la Salud</contributor>
<subject>Industria 5.0</subject>
<subject>TAI</subject>
<subject>Eye-tracking</subject>
<subject>Chatbot</subject>
<subject>Carga cognitiva</subject>
<subject>Apoyo emocional</subject>
<description>This study analyses the multimodal evaluation of cognitive load in complex visuomotor &#xd;
test, specifically focusing on implicit bias within human-IA interaction in the context of &#xd;
Industry 5.0. The research aims to understand how unconscious prejudices, measured &#xd;
through the Implicit Association Test (IAT or TAI, Spanish version), modulate user &#xd;
experience and how intelligent systems can act as emotional regulators. Using a multiple &#xd;
single case experimental design (n=3) three female university students aged 20 were &#xd;
evaluated. The methodology integrated subjective measures via NASA-TLX, &#xd;
physiological responses using Galvanic Skin Response (GSR) and &#xd;
electroencephalography (EEG), and visual behaviour through eye-tracking technology. &#xd;
In addition, a conversational chatbot named EsencIA was developed to provide &#xd;
psychological support based on cognitive-behavioural therapy for participants &#xd;
experiencing high frustration. Results indicate that participants perceive the TAI as a &#xd;
demanding task with medium-high mental load, where the temporal demand and effort &#xd;
are prominent. Quantitative data show a correlation between the intensity of implicit bias &#xd;
and visual exploration patterns, suggesting that more consolidated biases require greater &#xd;
cognitive supervision and increased saccadic movements. These findings highlight the &#xd;
importance of integrating multimodal metrics to understand cognitive and emotional &#xd;
processing, confirming the potential of IA as a support tool in high-demand environment &#xd;
to mitigate stress and improve user interaction.</description>
<date>2026-07-13</date>
<date>2026-07-13</date>
<date>2026-05-18</date>
<type>info:eu-repo/semantics/other</type>
<identifier>https://hdl.handle.net/10259/11912</identifier>
<language>spa</language>
<rights>http://creativecommons.org/licenses/by-nc-nd/4.0/</rights>
<rights>info:eu-repo/semantics/openAccess</rights>
<rights>Attribution-NonCommercial-NoDerivatives 4.0 Internacional</rights>
</thesis></metadata></record></GetRecord></OAI-PMH>