Stabilizing brain-computer interfaces through nonlinear manifold alignment with dynamics
Brianna Karpowicz,Yahia H. Ali,Lahiru N. Wimalasena,Mohammad Reza Keshtkaran,Andrew R. Sedler,Kevin Bodkin,Xuan Ma,Lee E. Miller,Chethan Pandarinath · COSYNE 2022
Fri, Mar 18, 2022
Intracortical brain-computer interfaces (iBCIs) can restore voluntary movement to people with paralysis by translating their brain activity into a control signal for an external device. Maintaining stable iBCI performance is challenging due to instabilities at the neural interface, such as shifts in electrode position in the brain or malfunctions of electrodes. Such instabilities result in a degradation of decoding performance, requiring that device use be interrupted to allow for the collection of recalibration data for the iBCI decoder. To address this challenge, an emerging class of methods