MyoSem: Aligning Electromyography with Natural-Language Action Semantics

MyoSem is an EMG–action semantic alignment framework that maps hand electromyography signals and multi‑view natural‑language action descriptions into a shared feature space for bidirectional retrieval. It constructs semantic prototypes from text, encodes EMG with local activation‑aware representations, and aggregates evidence using semantic queries. Evaluated on multiple datasets and protocols, MyoSem outperforms existing methods in bidirectional EMG‑text retrieval, demonstrating its effectiveness in moving EMG hand action understanding toward language‑queryable semantic retrieval.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

• safety