Abstract: Current brain-machine interfaces (BMIs) often rely on decoders trained for single tasks, limiting their flexibility in real-world applications. We propose an online learning framework that ...
Abstract: To enable low-power, closed-loop control in implantable brain-machine interfaces (BMIs), we explore efficient training strategies for spiking neural network (SNN) decoders under realistic ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results