CNN-attention model decodes EEG to hand kinematics with within-subject PCCs above 0.98 on two axes, improved to 0.93 overall by a motion-state FSM copilot that drops under 20% of points, enabling simulated Franka Panda control.
Toward the Next Generation of Retinal Neuroprosthesis: Visual Com- putation with Spikes
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Copilot-Assisted Second-Thought Framework for Brain-to-Robot Hand Motion Decoding
CNN-attention model decodes EEG to hand kinematics with within-subject PCCs above 0.98 on two axes, improved to 0.93 overall by a motion-state FSM copilot that drops under 20% of points, enabling simulated Franka Panda control.