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Machine learning algorithms for myoelectric pattern recognition require substantial user-specific training data, limiting broader applications of electromyography (EMG) in human–computer interfacing. Here, we present a framework for EMG-mediated motor intent decoding designed to function for new users without collecting user-specific training data. We introduce a Transformer-based architecture, te
