A closed-loop emulator that accurately predicts brain-machine interface decoder performance
Ken-Fu Liang,Jonathan C. Kao · COSYNE 2022
Intracortical brain-machine interfaces (iBMIs) aim to provide naturalistic communication and movement for those with paralysis by decoding neural spikes into actions 1–10. iBMIs traditionally require closed-loop in vivo experiments to develop, design, optimize, and benchmark decoder algorithms. Although offline evaluation provides insight into what algorithms are promising, the discrepancy between offline and online performance may lead to incorrect conclusions that mislead algorithm design 11–15. We therefore aim to build an emulator that accurately characterizes online decoder performance wi
Thu, Mar 17, 2022