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arXiv CS.AI
7/10/2026
A Graph Neural Network Model for Real-Time Gesture Recognition Based on sEMG Signals

A Graph Neural Network Model for Real-Time Gesture Recognition Based on sEMG Signals

Short summary

Researchers developed a Graph Neural Network for real-time hand gesture recognition from forearm EMG signals, achieving 99% accuracy in 48ms on M1 Pro. The system was validated on 8 subjects with 8-electrode sensors and surpassed existing gesture recognition methods, making it suitable for prosthetics and augmented reality control.

  • •GNN model achieves 99% accuracy on hand gesture recognition from sEMG signals
  • •Real-time performance: 48ms latency on M1 Pro CPU, suitable for prosthetics and AR
  • •Outperforms state-of-the-art techniques in 8-subject validation study

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