EEG-based measure of cognitive workload during a mental arithmetic task

Abstract

We collected EEG data from 16 subjects while they performed a mental arithmetic task at five different levels of difficulty. A classifier was trained to discriminate between three conditions: relaxed, low workload and high workload, using spectral features of the EEG. We obtained an average classification accuracy of 62%. A continuous workload index was obtained by low-pass filtering the classifier's output. The average correlation coefficient between the resulting workload index and the difficulty level of the task was 0.6. © 2011 Springer-Verlag.