SIM2VR: Towards Automated Biomechanical Testing in VR

Automated biomechanical testing has great potential for the development of VR applications, as initial insights into user behaviour can be gained in silico early in the design process. In particular, it allows prediction of user movements and ergonomic variables, such as fatigue, prior to conducting user studies. However, there is a fundamental disconnect between simulators hosting state-of-the-art biomechanical user models and simulators used to develop and run VR applications. Existing user simulators often struggle to capture the intricacies of real-world VR applications, reducing ecological validity of user predictions. In this paper, we introduce sim2vr, a system that aligns user simulation with a given VR application by establishing a continuous closed loop between the two processes. This, for the first time, enables training simulated users directly in the same VR application that real users interact with. We demonstrate that sim2vr can predict differences in user performance, ergonomics and strategies in a fast-paced, dynamic arcade game. In order to expand the scope of automated biomechanical testing beyond simple visuomotor tasks, advances in cognitive models and reward function design will be needed.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3654777.3676452
Citations
5
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
1.71

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SIM2VR: Towards Automated Biomechanical Testing in VR

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5 citations
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article

SIM2VR: Towards Automated Biomechanical Testing in VR

Antti Oulasvirta, Aleksi Ikkala, Jörg Müller, Perttu Hämäläinen, Florian Fischer, Arthur Fleig, Roderick Murray‐Smith, Miroslav Bachinski, Markus Klar
article en
5 citations

Abstract

Automated biomechanical testing has great potential for the development of VR applications, as initial insights into user behaviour can be gained in silico early in the design process. In particular, it allows prediction of user movements and ergonomic variables, such as fatigue, prior to conducting user studies. However, there is a fundamental disconnect between simulators hosting state-of-the-art biomechanical user models and simulators used to develop and run VR applications. Existing user simulators often struggle to capture the intricacies of real-world VR applications, reducing ecological validity of user predictions. In this paper, we introduce sim2vr, a system that aligns user simulation with a given VR application by establishing a continuous closed loop between the two processes. This, for the first time, enables training simulated users directly in the same VR application that real users interact with. We demonstrate that sim2vr can predict differences in user performance, ergonomics and strategies in a fast-paced, dynamic arcade game. In order to expand the scope of automated biomechanical testing beyond simple visuomotor tasks, advances in cognitive models and reward function design will be needed.

University of Cambridge (GB), University of Bergen (NO), University of Bayreuth (DE), University of Glasgow (GB), Leipzig University (DE), Aalto University (FI)
European Commission, Finnish Center for Artificial Intelligence, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 16%
Motor Control and Adaptation
1.71
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