2026-04-28T21:50:56Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/109012025-09-30T00:05:36Zcom_10259_4219com_10259_5086com_10259_2604col_10259_7349

Lucas Pérez, Gadea 0e87b76f-5ddb-4811-89d1-ed1ae4c45ea3 600 Ramírez Sanz, José Miguel 750 600 0000-0003-0189-8046 Serrano Mamolar, Ana 820 600 0000-0002-0027-7128 Arnaiz González, Álvar 39 600 0000-0001-6965-0237 Bustillo Iglesias, Andrés 81 600 0000-0003-2855-7532 2025-09-29T11:59:57Z 2025-09-29T11:59:57Z 2024-09-11 978-3-031-71707-9 978-3-031-71706-2 https://hdl.handle.net/10259/10901 10.1007/978-3-031-71707-9_32 Comunicación presentada en: International Conference on Extended Reality, XR Salento 2024, held in Lecce, Italy during September 4–7, 2024 This work presents a conceptual framework that integrates Artificial Intelligence (AI) into immersive Virtual Reality (iVR) training systems, aiming to enhance adaptive learning environments that dynamically respond to individual users’ physiological states. The framework uses real-time data acquisition from multiple sources, including physiological sensors, eye-tracking and user interactions, processed through AI algorithms to personalise the training experience. By adjusting the complexity and nature of training tasks in real time, the framework seeks to maintain an optimal balance between challenge and skill, fostering an immersive learning environment. This work details some methodologies for data acquisition, the preprocessing required to synchronise and standardise diverse data streams, and the AI training techniques essential for effective real-time adaptation. It also discusses logistical considerations of computational load management in adaptive systems. Future work could explore the scalability of these systems and their potential for self-adaptation, where models are continuously refined and updated in real-time based on incoming data during user interactions. This work was supported by the Ministry of Science and Innovation of Spain under project PID2020-119894GB-I00, co-financed through European Union FEDER funds and the project Humanaid (TED2021-129485B-C43) cofunded by “NextGenerationEU”/PRTR funds. It was also supported through REMAR Project (CPP2022-009724) funded by the Ministry of Science and Innovation of Spain (MCIN/AEI/ 10.13039/501100011033) and by the European Union NextGenerationEU/PRTR. And, finally, it was supported through the Consejería de Educación of the Junta de Castilla y León and the European Social Fund through a pre-doctoral grant (EDU/875/2021). application/pdf eng Springer Extended Reality: XR Salento 2024, proceedings, Part I, V. 15027, p 376–384 https://doi.org/10.1007/978-3-031-71707-9_32 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-119894GB-I00/ES/APRENDIZAJE AUTOMATICO CON DATOS ESCASAMENTE ETIQUETADOS PARA LA INDUSTRIA 4.0/ info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/TED2021-129485B-C43/ES/Sistemas dinámicos inteligentes centrados en el usuario para la Prevención de Riesgos Laborales/ info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/CPP2022-009724/ES/Simuladores inteligentes adaptativos en Realidad Extendida para la mejora de procesos de Mantenimiento de Alto Riesgo/REMAR Machine learning Immersive virtual reality Game-based learning Eye-tracking Stress Inteligencia artificial en la enseñanza Artificial intelligence-Educational applications Personalising the Training Process with Adaptive Virtual Reality: A Proposed Framework, Challenges, and Opportunities info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/acceptedVersion info:eu-repo/semantics/openAccess 15027 376 384 THUMBNAIL Lucas-Personalising_Training_Process_Adaptive_Virtual_Reality_2024.pdf.jpg Lucas-Personalising_Training_Process_Adaptive_Virtual_Reality_2024.pdf.jpg IM Thumbnail image/jpeg 3643 https://riubu.ubu.es/bitstream/10259/10901/3/Lucas-Personalising_Training_Process_Adaptive_Virtual_Reality_2024.pdf.jpg b3c822c9ea85c319889429c5c781ca67 MD5 3 LICENSE license.txt license.txt text/plain; charset=utf-8 1362 https://riubu.ubu.es/bitstream/10259/10901/2/license.txt 5d013bfa6e473ff0db22cd82a4d71a70 MD5 2 ORIGINAL Lucas-Personalising_Training_Process_Adaptive_Virtual_Reality_2024.pdf Lucas-Personalising_Training_Process_Adaptive_Virtual_Reality_2024.pdf application/pdf 479822 https://riubu.ubu.es/bitstream/10259/10901/1/Lucas-Personalising_Training_Process_Adaptive_Virtual_Reality_2024.pdf 6bd9d1d73f664601be8c41f724b96daa MD5 1 10259/10901 oai:riubu.ubu.es:10259/10901 2025-09-30 02:05:36.21 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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