Vidal-Balea, AidaFraga-Lamas, PaulaFernández-Caramés, Tiago M.2024-10-31A. Vidal-Balea, P. Fraga-Lamas and T. M. Fernández-Caramés, "Advancing NASA-TLX: Automatic User Interaction Analysis for Workload Evaluation in XR Scenarios," 2024 IEEE Gaming, Entertainment, and Media Conference (GEM), Turin, Italy, 2024, pp. 1-6, doi: 10.1109/GEM61861.2024.105854259798350374537http://hdl.handle.net/2183/39901Presented at: 2024 IEEE Gaming, Entertainment, and Media Conference, GEM 2024, Turin, 5 June 2024 through 7 June 2024This version of the paper has been accepted for publication.[Abstract]: Calculating the effort required to complete a task has always been somewhat difficult, as it depends on each person and becomes very subjective. For this reason, different methodologies were developed to try to standardize these procedures. This article addresses some of the problems that arise when applying NASA-Task Load Index (NASA-TLX), a methodology to calculate the mental workload of tasks performed in industrial environments. In addition, an improvement of this methodology is proposed to adapt it to the new times and to emerging Extended Reality (XR) technologies. Finally, a system is proposed for automatic collection of user performance metrics, providing an autonomous method that collects this information and does not depend on the users' willingness to fill in a feedback questionnaire.eng© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published paper is available online at: https://doi.org/10.1109/GEM61861.2024.10585425Augmented realityExtended realityMental workloadMicrosoft HoloLensMixed realityNASA-TLXXR NASA-TLXconference outputopen access10.1109/GEM61861.2024.10585425