FatigueFusion: Latent Space Fusion for Fatigue-Driven Motion Synthesis
Investigating the impact of fatigue on human physiological function and motor behavior is crucial for developing biomechanics and medical applications aimed at mitigating fatigue, reducing injury risk, and creating sophisticated ergonomic designs, as well as for producing physically-plausible 3D animation sequences. While the former has a prominent position in state-of-the-art literature, fatigue-driven motion generation is still an underexplored area. In this study, we present FatigueFusion, a deep-learning architecture for the fusion of fatigue features within a latent representation space, enabling the creation of a variation of novel fatigued movements, intermediate fatigued states, a...
| Authors | Iliana Loi, Konstantinos Moustakas |
|---|---|
| Primary category | cs.GR |
| Published | 11 April 2026 |
| Last updated at source | 11 April 2026 |
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