Detection of multitask mental workload using gamma band power features

Cognitive fatigue occurs in various situations and is an essential condition to detect. In this study, how single and multi-tasking tests affect cognitive workload was examined, and multi-tasking was detected using electroencephalography (EEG) signals. In the cognitive workload paradigm, single-task tests with blocks 1 and 2 and multi-tasking tests with block 3 were created. EEG signals obtained from these blocks were treated as different frequency bands and lengths, and binary classification was performed. Two binary classifications were made: block 1–block 3 and block 2–block 3. According to the results, the highest classification accuracy for block 1–block 3 was obtained as 97.11