Datasets for the GAME+ Project (PID2023-149976OB-C21)

This repository contains six datasets produced within the GAME+ project (Advanced Libraries for Upgrading Game Engine Technology), funded by the Agencia Estatal de Investigación (AEI) of Spain under grant PID2023-149976OB-C21. The project is a coordinated research effort between the Universitat Jaume I (UJI, subproject coordinator: Miguel Chover) and the Universitat de Girona (UdG, subproject coordinator: Mateu Sbert). GAME+ aims to develop advanced plugins and libraries for game engines in the areas of Artificial Intelligence, Realistic Graphics, and eXtended Reality, validated through active video games focused on fitness and health applications. All datasets contain anonymized questionnaire responses collected from participants in controlled experiments using the Fitoon treadmill exergame. Data were collected via Google Forms and exported to CSV format. Variables include Likert-scale items and demographic data (age, gender, height, weight). Each dataset is associated with one of the following publications: Marín-Lora, C., Villar-López, M. B., Montaña-Miranda, N., Martín, M. Y., & Chover, M. (2026). Evaluating game experience in a treadmill exergame: Virtual reality versus screen-based display. Virtual Reality. https://doi.org/10.1007/s10055-026-01355-w GAME_Fitoon_GEQ_VRfirst_2025.csv: Game Experience Questionnaire (GEQ) responses from participants who experienced the VR condition first. GAME_Fitoon_GEQ_ScreenFirst_2025.csv: GEQ responses from participants who experienced the screen-based condition first. GAME_Fitoon_EEQG_VRfirst_2025.csv: Exertion Experience Questionnaire for Games (EEQ-G) responses from participants who experienced the VR condition first. GAME_Fitoon_EEQG_ScreenFirst_2025.csv: EEQ-G responses from participants who experienced the screen-based condition first. Martin, M. Y., Marín-Lora, C., Villar-López, M. B., & Chover, M. (2025). Optimizing the interaction system for treadmill video games using a smartphone's front camera. Sensors, 26(1), 20. https://doi.org/10.3390/s26010020 GAME_SpeedEstimation_FFT-vs-Camera_2024.csv: Speed estimation data comparing FFT-based and video camera-based methods for detecting running cadence. Martin, M. Y., Marín-Lora, C., & Chover, M. (2025). A comparative analysis of game experience in treadmill running applications. Entertainment Computing, 52. https://doi.org/10.1016/j.entcom.2024.100888 GAME_GEQ_Treadmill-vs-Floor_2022.csv: GEQ responses comparing game experience between treadmill and floor running conditions.