Modified mental workload index: Measure it with task difficulty degree and performance, Verified it with cross-time classification

The brain state is very important for daily life, especially for mentally exhausting tasks. Researches usually use task difficult as a brain state index, while the performance for detecting the brain state is not satisfying. In order to comprehensively reflect the functional state of the operator, We defined a new operator functional state (OFS) based on the task difficulty degree and behavioral performance. We analyzed the power spectrum of different OFS and examined the classification accuracies under both non-cross-time and cross-time OFS conditions. The average accuracy of non-cross-time with two-class can reach 95.61% and reached to 78.43% for four-class classification. For the cross-time classification, the average accuracy across time of the two-class classification reaches 91.38%, while for the four-class classification it only has an accuracy of 54.22%, which is also higher than the accuracies only using task difficulty as the brain state index. The results showed that the task difficulty and task performance are both important and should comprehensively considered for the OFS index, it will help to understand the brain state in a more accurate way.