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.

Automated Task Load Detection with Electroencephalography: Towards Passive Brain–Computer Interfacing in Robotic Surgery

“…The vast majority of these studies evaluate spectral power differences in certain frequency bands that have shown to be sensitive to different cognitive load conditions. In particular, an increase of frontal theta activity is observed while parietal alpha power decreases as more cognitive resources are allocated to the task [30][31][32][33]. Hence, we hypothesize that passive BCI can be used to reliably differentiate between OHKT and MISKT, and that during performance of technically challenging tasks (MISKT, dual-tasking) an increased frontal theta activity with concurrent decreased parietal alpha activity will be observed in the EEG.…”

Feasibility and pragmatics of classifying working memory load with an electroencephalograph

“…To test if alpha and theta bands were predictive of memory and cognitive loads in real world computing tasks, Smith et al [27] compared EEG data when task difficulty was manipulated within a multi-attribute task battery (MATB) multitasking environment. They report successfully creating a user-specific index of task load, the average values of which increase with increasing task difficulty and differed significantly between the difficulty manipulations.…”

“…[6,7,20,21,27]), previous work has typically relied on costly equipment and techniques that make it difficult for non-EEG-experts to replicate and use this work. Additionally, this work has often required experimenters to collect large amounts of classifier training data (sometimes on the order of days), a process that is often prohibitively expensive.…”

The Analysis of Driving Workload and Gamma Waves on Curved Sections in Expressway

“…Increases in driving difficulty and mental workload were most often associated with a decrease of alpha and an increase of theta power (Klimesch, 1999;Scerbo et al, 2003;Smith et al, 2001). Gamma waves relate to neural consciousness via the mechanism for conscious attention.…”