AI RESEARCH
Translating Signals to Languages for sEMG-Based Activity Recognition
arXiv CS.CV
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ArXi:2605.22403v1 Announce Type: new Surface electromyography (sEMG) signal-based activity recognition has attracted increasing research attention in recent years. To develop accurate sEMG signal-based activity recognizers, numerous approaches have been proposed. Some studies focus on designing larger and expressive model architectures to enhance the representational capacity of sEMG signals, while others aim to enrich model priors through large-scale pre