A Dictionary Driven Mental Typewriter Based on Code-Modulated Visual Evoked Potentials (cVEP)

摘要

Brain-computer interfaces (BCIs) based on code-modulated potentials (cVEPs) identify a target usually in the synchronous way (i.e. after a preset time period the system will produce a command output). Hence, users have only a limited amount of time to fixate a desired target. For the practical usability of BCI spellers it is important to distinguish between intentional and unintentional fixations. In this paper we propose the use of threshold-based target identification methods for the cVEP paradigm. These methods were tested with a dictionary driven spelling application utilizing eight flashing targets. In this respect, an n-gram word prediction model was implemented. The performance of ten healthy participants was evaluated in an online experiment. All participants completed different German sentences using the cVEP BCI with a mean information transfer rate (ITR) of 31.08 bpm.