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Evidence record 3427 · automatically gathered

MyoSem: Aligning Electromyography to Natural-Language Action Semantics for Hand Action Understanding

Electromyography (EMG) directly reflects muscle activation and is a key sensing modality for gesture recognition, prosthetic control, and wearable interaction. Existing EMG methods, however, commonly formulate hand action understanding as classification over fixed labels, making it difficult to support querying, retrieval, and generalization based on action descriptions. We present MyoSem, an EMG--action semantic alignment framework that maps low-level EMG signals into a shared semantic space co

Record details

Published: 29 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment
Retrieved: 14 July 2026

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Shared topic: Safety & alignment

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Shared topic: Safety & alignment

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How to cite this record

ethics.ai (29 May 2026), “MyoSem: Aligning Electromyography to Natural-Language Action Semantics for Hand Action Understanding,” evidence record 3427, https://ethics.ai/record/3427 (originally published by arXiv).

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