On the Identifiability of User Adaptation in Co-Adaptive Neural Interfaces (opens in new tab)

We analyze identifiability in co-adaptive human-machine systems. We show that closed-loop encoder estimates do not uniquely identify user adaptation, but instead reflect properties of the joint system. We discuss implications for interpreting behavioral adaptation and propose conditions for identification.