MyoSem: Aligning Electromyography with Natural-Language Action Semantics
Electromyography (EMG) records muscle activation for hand gesture recognition, prosthetic control, and wearable interaction. Existing EMG methods usually formulate hand action understanding as prediction over fixed gesture labels, leaving EMG signals and action-semantic text unaligned in a common feature space and limiting bidirectional querying between signals and hand-action descriptions. We present MyoSem, an EMG--action semantic alignment framework that maps hand EMG and multi-view natural-language action descriptions into a shared feature space for retrieval. MyoSem builds semantic prototypes from multi-view descriptions, encodes EMG with local activation-aware representations, and u...
| Authors | Chiyue Wang, Yang Gao, Zhanpeng Jin |
|---|---|
| Primary category | cs.CV |
| Published | 29 May 2026 |
| Last updated at source | 9 October 2026 |
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