Investigating mental workload across task modalities: a multimodal analysis using pupillometry.

Area of Science:

• Cognitive Psychology
• Human-Computer Interaction
• Neuroscience

Background:

• Mental workload is complex, with measures like task performance, perceived workload, and physiological responses showing varied sensitivities.
• Existing research often struggles to capture the multidimensional nature of mental workload across different information processing modalities.

Purpose of the Study:

• To investigate how varying task loads affect performance, perceived workload, and pupil-based physiological responses across different information modalities.
• To identify robust measures of mental workload that are consistent across verbal and visual information processing.

Main Methods:

• A within-subjects experimental design was employed, featuring three cognitive tasks (digit span, matrix span, dual n-back) at three distinct task load levels.
• Measures included task performance (accuracy, reaction time), perceived workload (NASA-TLX), and pupillometry (peak pupil diameter, peak pupil latency).

Main Results:

• Consistent associations between task load and workload measures were observed across verbal and visual modalities.
• Peak pupil latency, accuracy, and NASA-TLX demonstrated robustness across modalities, indicating reliable mental workload assessment.
• Peak pupil diameter showed less consistent patterns, with significant differences observed between modalities.

Conclusions:

• Mental workload assessment benefits from a multivariate approach, integrating performance, subjective, and physiological measures.
• Peak pupil latency and accuracy are promising objective measures for mental workload, particularly in verbal and visual tasks.
• Task modality significantly influences certain physiological workload indicators, necessitating careful consideration in experimental design and interpretation.