Information Theoretic Analysis of the Impact of Refractory Effects on the P300 Speller
The P300 speller is a brain-computer interface that enables people with severe neuromuscular disorders to communicate based on eliciting and detecting event-related potentials (ERP) in electroencephalography (EEG) measurements, in response to rare target stimulus events. One of the challenges to fast and reliable communication is the fact that the P300 ERP has a refractory period that induces temporal dependence in the user’s EEG responses. Refractory effects negatively affect the performance of the speller. This paper shows how the refractory effect in the P300 speller can be modeled using a communication channel with memory. By studying the maximum information rate on this channel we gain insight into the fundamental constraint imposed by the refractory effect. Moreover, we show that one can design codebooks based on the input distribution that maximize the mutual information in the model. We provide simulation result comparing these code constructions to existing code constructions in the literature.