Using theta and alpha band power to assess cognitive workload in multitasking environments

Area of Science:

• Human Factors and Ergonomics
• Neuroscience
• Cognitive Psychology

Background:

• Cognitive workload assessment is crucial for human-machine interface design and safety.
• Electroencephalography (EEG) is frequently used to measure cognitive workload, with studies linking increased theta and decreased alpha band power to higher workload.
• Inconsistent findings in previous EEG studies suggest potential influences of individual differences and small sample sizes.

Purpose of the Study:

• To investigate the relationship between cognitive workload, task performance, and EEG signals in a multitasking environment.
• To address inconsistencies in previous research by accounting for individual differences in performance.

Main Methods:

• Utilized electroencephalography (EEG) to record brain activity.
• Employed a multitasking simulation task, increasing concurrent sub-tasks from one to four.
• Collected subjective ratings, performance scores, pupil size, and EEG data from twenty participants.

Main Results:

• Increased EEG theta and alpha band power correlated with higher cognitive resource engagement for one to three subtasks.
• EEG measures plateaued when task performance began to decline.
• Higher task performance was consistently associated with lower theta and alpha band power.

Conclusions:

• EEG alpha and theta band power are sensitive indicators of cognitive workload in multitasking scenarios.
• Individual performance levels are critical factors influencing EEG-based workload assessment.
• Accounting for performance differences enhances the reliability of EEG for measuring cognitive workload.