2026-07-16T00:17:52Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/119122026-07-14T00:05:28Zcom_10259_9401com_10259_5087com_10259_2728col_10259_9403

Evaluación multimodal de la carga cognitiva en el desempeño de tareas visomotoras complejas: un estudio sobre el sesgo implícito en la interacción humano-ia Martínez Mora, Sara Morales Balbás, Samuel Sanz Palacios, Teresa Urizarna Sánchez, Alba Sáiz Manzanares, María Consuelo Olivares Gil, Alicia Universidad de Burgos. Departamento de Ciencias de la Salud Industria 5.0 TAI Eye-tracking Chatbot Carga cognitiva Apoyo emocional Inteligencia artificial Psicología fisiológica Artificial intelligence Psychophysiology 8959 - Sistemas inteligentes aplicados a la psicología This study analyses the multimodal evaluation of cognitive load in complex visuomotor test, specifically focusing on implicit bias within human-IA interaction in the context of Industry 5.0. The research aims to understand how unconscious prejudices, measured through the Implicit Association Test (IAT or TAI, Spanish version), modulate user experience and how intelligent systems can act as emotional regulators. Using a multiple single case experimental design (n=3) three female university students aged 20 were evaluated. The methodology integrated subjective measures via NASA-TLX, physiological responses using Galvanic Skin Response (GSR) and electroencephalography (EEG), and visual behaviour through eye-tracking technology. In addition, a conversational chatbot named EsencIA was developed to provide psychological support based on cognitive-behavioural therapy for participants experiencing high frustration. Results indicate that participants perceive the TAI as a demanding task with medium-high mental load, where the temporal demand and effort are prominent. Quantitative data show a correlation between the intensity of implicit bias and visual exploration patterns, suggesting that more consolidated biases require greater cognitive supervision and increased saccadic movements. These findings highlight the importance of integrating multimodal metrics to understand cognitive and emotional processing, confirming the potential of IA as a support tool in high-demand environment to mitigate stress and improve user interaction. 2026-07-13T09:15:12Z 2026-07-13T09:15:12Z 2026-05-18 info:eu-repo/semantics/other info:eu-repo/semantics/acceptedVersion https://hdl.handle.net/10259/11912 spa Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess application/pdf https://riubu.ubu.es/bitstream/10259/11912/4/Martinez-Morales-Sanz-Urizarna_Evaluacion_multimodal_carga_cognitiva_2026.pdf.jpg Hispana TEXT http://creativecommons.org/licenses/by-nc-nd/4.0/ RIUBU. Repositorio Institucional de la Universidad de Burgos https://hdl.handle.net/10259/11912