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Pose2Muscle: Structured Spatio-Temporal Decoding for Discrete Muscle Activity Estimation from Human Pose
Muscle activity is fundamental to human movement, and understanding its patterns is critical for injury prevention and rehabilitation. Conventional muscle activity monitoring relies on specialized sensors such as surface electromyography, which limits its practicality for long-term real-world use. Existing studies suggest that muscle-related information can be inferred from human pose. However, the substantial gap between externally observable pose and internal muscle activation, limits the accuracy and generalization of current approaches. In this study, we propose Pose2Muscle, a pose-driven
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T08:58:45.000Z
First collected: 2026-09-20T08:01:03.945Z. This is not the publication date.