Toward Optimized VR/AR Ergonomics: Modeling and Predicting User Neck Muscle Contraction
Yunxiang Zhang, Kenneth Chen, Qi Sun
2023Year
14Citations
3Top-tier citations
Abstract
Predicting the neck muscle contraction and discomfort levels of VR users. (a) A VR user chooses between two candidate head motion trajectories of seemingly similar muscular workload for a visual task. (b) Our computational model predicts the user's potential neck muscle contraction level and thus perceived neck muscle discomfort before the movements happen. 3D asset credits to Mixall, Bizulka, RootMotion at Unity, and shockwavegamez01, joseVG at Sketchfab.
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Cited by top-tier papers3
- NICER: A New and Improved Consumed Endurance and Recovery Metric to Quantify Muscle Fatigue of Mid-Air InteractionsYi Li, Benjamin Tag, Shaozhang Dai, Robert George Crowther et al.SIGGRAPH 2024 · 15 citations
- Dragon's Path: Synthesizing User-Centered Flying Creature Animation Paths for Outdoor Augmented Reality ExperiencesMinyoung Kim, Rawan Alghofaili, Changyang Li, Lap-Fai YuSIGGRAPH 2024 · 4 citations
- GraspR: A Computational Model of Spatial User Preferences for Adaptive Grasp UI DesignArthur Caetano, Yunhao Luo, Adwait Sharma, Misha SraUIST 2025 · 1 citation
Builds on3
- Hands-free interaction in immersive virtual reality: A systematic reviewPedro Monteiro, Guilherme Gonçalves, Hugo Coelho, Miguel Melo et al.IEEE VR 2021 · 116 citations
- NeuroPose: 3D Hand Pose Tracking using EMG WearablesYilin Liu, Shijia Zhang, Mahanth GowdaWWW 2021 · 84 citations
- Exertion-aware path generationWanwan Li, Biao Xie, Yongqi Zhang, Walter Meiss et al.SIGGRAPH 2020 · 27 citations
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