Estimation of mental workload induced by different presentation rates in rapid serial visual presentation tasks

Brain-computer interface (BCI) based on rapid serial visual presentation (RSVP) is an efficient information detection technology by detecting event related brain response evoked by target stimuli. In the protocol design of the RSVP-BCI a range of parameters could influence the task difficulty, which may result in the changes of mental workload for subjects. This paper focused on the presentation rate in the RSVP paradigm aiming to investigate its influence on mental workload, and the separability of brain states during RSVP tasks with different setup of presentation rate. 64-channel Electroencephalographic (EEG) data were recorded during RSVP tasks with three levels of presentation rate in ten healthy subjects. The results show that different presentation rates indeed contribute to significant differences on mental workload revealed by one-way repeated measures analysis of variance (ANOVA) on z-scored RSME. Higher presentation rate results in the significant decrease on both behavioral and single-trial recognition performance of target images. Classification results on three levels of mental workload show that the mean accuracy reaches 65.5% and the highest accuracy reaches 88.3%. This work implies that mental workload induced by different presentation rates during RSVP tasks could be accurately recognized, and provides a possible method to monitor the mental workload in the application areas of RSVP-BCI.