Eye Tracking-Based Stress Classification of Athletes in Virtual Reality

Stöve M, Wirth M, Farlock R, Antunovic A, Müller V, Eskofier B (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Proceedings of the ACM on Computer Graphics and Interactive Techniques Association for Computing Machinery (ACM)

Book Volume: 5

Pages Range: 1-17

Issue: 2

DOI: 10.1145/3530796

Abstract

Monitoring stress is relevant in many areas, including sports science. In that scope, various studies showed the feasibility of stress classification using eye tracking data. In most cases, the screen-based experimental design restricted the motion of participants. Consequently, the transferability of results to dynamic sports applications remains unclear. To address this research gap, we conducted a virtual reality-based stress test consisting of a football goalkeeping scenario. We contribute by proposing a stress classification pipeline solely relying on gaze behaviour and pupil diameter metrics extracted from the recorded data. To optimize the analysis pipeline, we applied feature selection and compared the performance of different classification methods. Results show that the Random Forest classifier achieves the best performance with 87.3% accuracy, comparable to state-of-the-art approaches fusing eye tracking data and additional biosignals. Moreover, our approach outperforms existing methods exclusively relying on eye measures.

Authors with CRIS profile

Maike Stöve Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Markus Wirth Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Victoria Müller Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Björn Eskofier Machine Learning and Data Analytics Lab

Related research project(s)

Adaptive AI Systems in Sport (BISS) Dec. 1, 2021 - May 31, 2024 Digital Twin – Novel data fusion algorithms and immersive interaction concepts for the holistic description and evaluation of athletes through self-learning systems (Digital Twin) Digital Twin - holistische Beschreibung und Bewertung von Athleten Dec. 1, 2018 - Dec. 31, 2021

Involved external institutions

Adidas AG DE Germany (DE)

How to cite

APA:

Stöve, M., Wirth, M., Farlock, R., Antunovic, A., Müller, V., & Eskofier, B. (2022). Eye Tracking-Based Stress Classification of Athletes in Virtual Reality. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 5, 1-17. https://doi.org/10.1145/3530796

MLA:

Stöve, Maike, et al. "Eye Tracking-Based Stress Classification of Athletes in Virtual Reality." Proceedings of the ACM on Computer Graphics and Interactive Techniques 5 (2022): 1-17.

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