title: Monitoring task loading with multivariate EEG measures during complex forms of human-computer interaction.
abstract: Electroencephalographic (EEG) recordings were made while 16 participants performed versions of a personal-computer-based flight simulation task of low, moderate, or high difficulty. As task difficulty increased, frontal midline theta EEG activity increased and alpha band activity decreased. A participant-specific function that combined multiple EEG features to create a single load index was derived from a sample of each participant's data and then applied to new test data from that participant. Index values were computed for every 4 s of task data. Across participants, mean task load index values increased systematically with increasing task difficulty and differed significantly between the different task versions. Actual or potential applications of this research include the use of multivariate EEG-based methods to monitor task loading during naturalistic computer-based work.
authors.affiliation: San Francisco Brain Research Institute and SAM Technology, California 94108, USA. michael@eeg.com
authors.forename: M E
authors.initials: ME
authors.lastname: Smith
authors.forename: A
authors.initials: A
authors.lastname: Gevins
authors.forename: H
authors.initials: H
authors.lastname: Brown
authors.forename: A
authors.initials: A
authors.lastname: Karnik
authors.forename: R
authors.initials: R
authors.lastname: Du
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods; D005260:Female; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D013647:Task Performance and Analysis; D014584:User-Computer Interface