Correlation graphs built from windowed multi-channel sEMG plus a lightweight GNN yield 99% real-time accuracy on five hand gestures from eight subjects, exceeding three prior baselines.
3D skeleton-based video action recognition by graph convolution network,
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A Graph Neural Network Model for Real-Time Gesture Recognition Based on sEMG Signals
Correlation graphs built from windowed multi-channel sEMG plus a lightweight GNN yield 99% real-time accuracy on five hand gestures from eight subjects, exceeding three prior baselines.