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Phase-Guided Self-Supervised Latent Representation Learning for sEMG-Based Gait Decoding.
Surface electromyography (sEMG) provides a non-invasive measure of neuromuscular activity and is widely used for gait decoding in wearable and rehabilitation systems. Existing sEMG-based approaches rely on end-to-end supervised regression with dense kinematic labels, limiting scalability, generalization, and interpreta...