SEP 9, 2026 · PREPRINT
Deep Neural Networks for Learning Intent from sEMG Signals to Support Hardware Devices for Post-Stroke Neurorehabilitation
arXiv
This is an early-stage machine learning development study on a stroke rehabilitation dataset, demonstrating feasibility of finger-intent decoding from sEMG but lacking clinical validation, prospective outcomes, or hardware deployment results.
Reported
LSTM subset accuracy0.545
GNN macro F10.706
GNN macro AUPRC0.776