Physics-Embedded Neural Network
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Physics-Embedded Neural Networks for sEMG-based Continuous Motion Estimation
arXiv:2506.22459v1 Announce Type: cross Abstract: Accurately decoding human motion intentions from surface electromyography (sEMG) is essential for myoelectric control and has wide applications in rehabilitation robotics and assistive technologies. However, existing sEMG-based motion estimation methods often rely on subject-specific musculoskeletal (MSK) models that are difficult to calibrate, or purely data-driven models that lack physiological consistency. This paper introduces a novel...