AHCI RESEARCH GROUP

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proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2024

Geurts, E.; Warson, D.; Ruiz, G. Rovelo

Boosting Motivation in Sports with Data-Driven Visualizations in VR Proceedings Article

In: ACM Int. Conf. Proc. Ser., Association for Computing Machinery, 2024, ISBN: 979-840071764-2 (ISBN).

Abstract | Links | BibTeX | Tags: Artificial intelligence, Asynchronoi social interaction, Asynchronous social interaction, Cycling, Data driven, Dynamics, Extended reality, Group dynamics, Language Model, Large language model, large language models, Motivation, Natural language processing systems, Real-world, Real-world data, Social interactions, Sports, User interface, User interfaces, Virtual Reality, Visualization, Visualizations

@inproceedings{geurts_boosting_2024,

title = {Boosting Motivation in Sports with Data-Driven Visualizations in VR},

author = {E. Geurts and D. Warson and G. Rovelo Ruiz},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195387493&doi=10.1145%2f3656650.3656669&partnerID=40&md5=ec69e7abe61e572a94261ad6bbfed11c},

doi = {10.1145/3656650.3656669},

isbn = {979-840071764-2 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {ACM Int. Conf. Proc. Ser.},

publisher = {Association for Computing Machinery},

abstract = {In recent years, the integration of Artificial Intelligence (AI) has sparked revolutionary progress across diverse domains, with sports applications being no exception. At the same time, using real-world data sources, such as GPS, weather, and traffic data, offers opportunities to improve the overall user engagement and effectiveness of such applications. Despite the substantial advancements, including proven success in mobile applications, there remains an untapped potential in leveraging these technologies to boost motivation and enhance social group dynamics in Virtual Reality (VR) sports solutions. Our innovative approach focuses on harnessing the power of AI and real-world data to facilitate the design of such VR systems. To validate our methodology, we conducted an exploratory study involving 18 participants, evaluating our approach within the context of indoor VR cycling. By incorporating GPX files and omnidirectional video (real-world data), we recreated a lifelike cycling environment in which users can compete with simulated cyclists navigating a chosen (real-world) route. Considering the user's performance and interactions with other cyclists, our system employs AI-driven natural language processing tools to generate encouraging and competitive messages automatically. The outcome of our study reveals a positive impact on motivation, competition dynamics, and the perceived sense of group dynamics when using real performance data alongside automatically generated motivational messages. This underscores the potential of AI-driven enhancements in user interfaces to not only optimize performance but also foster a more engaging and supportive sports environment. © 2024 ACM.},

keywords = {Artificial intelligence, Asynchronoi social interaction, Asynchronous social interaction, Cycling, Data driven, Dynamics, Extended reality, Group dynamics, Language Model, Large language model, large language models, Motivation, Natural language processing systems, Real-world, Real-world data, Social interactions, Sports, User interface, User interfaces, Virtual Reality, Visualization, Visualizations},

pubstate = {published},

tppubtype = {inproceedings}

}