Comparison of concurrent cognitive load measures during n-back tasks

Area of Science:

• Human-Computer Interaction
• Cognitive Psychology
• Performance Measurement

Background:

• Cognitive load significantly impacts human performance across various domains like driving, aviation, and healthcare.
• Both cognitive overload and underload can lead to errors, reduced efficiency, and safety risks.
• Current methods for assessing cognitive load are indirect, relying on physiological, behavioral, performance, or subjective data, lacking objective comparison standards.

Purpose of the Study:

• To propose a novel, objective performance metric for evaluating and comparing diverse measures of cognitive load.
• To address the lack of a standardized method for assessing the efficacy of different cognitive load indicators.
• To enable better understanding and selection of appropriate cognitive load measurement techniques.

Main Methods:

• A performance metric based on the signal-to-noise ratio was developed for comparing cognitive load measures.
• Multiple cognitive load measures were evaluated using this metric.
• Data was collected from 28 participants performing n-back tasks of varying difficulty levels.

Main Results:

• The proposed signal-to-noise ratio metric provides a unified scale for comparing different cognitive load assessment methods.
• The study successfully compared various measures of cognitive load on the same scale.
• The results demonstrate the utility of the proposed performance evaluation method for individual assessment of cognitive load measures.

Conclusions:

• The developed signal-to-noise ratio metric offers an objective approach to evaluate the performance of cognitive load measures.
• This method can aid researchers and practitioners in selecting the most effective tools for cognitive load assessment.
• Objective comparison of cognitive load measures is crucial for improving human performance and safety in complex systems.