CortexVR: Immersive analysis and training of cognitive executive functions of soccer players using virtual reality and machine learning

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Abstract

Goal: This paper presents an immersive Virtual Reality (VR) system to analyze and train Executive Functions (EFs) of soccer players. EFs are important cognitive functions for athletes. They are a relevant quality that distinguishes amateurs from professionals. Method: The system is based on immersive technology, hence, the user interacts naturally and experiences a training session in a virtual world. The proposed system has a modular design supporting the extension of various so-called game modes. Game modes combine selected game mechanics with specific simulation content to target particular training aspects. The system architecture decouples selection/parameterization and analysis of training sessions via a coaching app from an Unity3D-based VR simulation core. Monitoring of user performance and progress is recorded by a database that sends the necessary feedback to the coaching app for analysis. Results: The system is tested for VR-critical performance criteria to reveal the usefulness of a new interaction paradigm in the cognitive training and analysis of EFs. Subjective ratings for overall usability show that the design as VR application enhances the user experience compared to a traditional desktop app; whereas the new, unfamiliar interaction paradigm does not negatively impact the effort for using the application. Conclusion: The system can provide immersive training of EF in a fully virtual environment, eliminating potential distraction. It further provides an easy-to-use analyzes tool to compare user but also an automatic, adaptive training mode.

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APA

Krupitzer, C., Naber, J., Stauffert, J. P., Mayer, J., Spielmann, J., Ehmann, P., … Latoschik, M. E. (2022). CortexVR: Immersive analysis and training of cognitive executive functions of soccer players using virtual reality and machine learning. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.754732

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