Exploring workload and attention measurements with uLog mouse data.

Area of Science:

• Human-Computer Interaction
• Cognitive Load Assessment
• Biometric Data Analysis

Background:

• Understanding user workload and attention is crucial for optimizing system design.
• Traditional methods for assessing these cognitive states can be intrusive or subjective.
• The uLog program offers a novel approach to logging user-system interactions, specifically mouse movements.

Purpose of the Study:

• To investigate the feasibility of using uLog data as a non-intrusive indicator of user workload and attention.
• To validate the potential of uLog data against established physiological measures.
• To establish a foundation for using interaction logging in cognitive state assessment.

Main Methods:

• A web-based study involving 20 participants.
• Logging user-system interactions using the uLog computer program.
• Measuring physiological responses including eye fixation, heart rate variability (HRV), and skin conductance.
• Correlating uLog data with physiological measures to assess workload and attention.

Main Results:

• Significant correlations were observed between uLog data and heart rate variability (HRV) during specific tasks.
• These findings suggest that mouse interaction patterns may reflect cognitive load.
• The study provides preliminary evidence for the utility of uLog data.

Conclusions:

• uLog data shows potential as a valid, non-intrusive indicator of user workload and attention.
• This research represents a promising first step in validating mouse-based interaction logging for cognitive state monitoring.
• Further research is warranted to explore the full capabilities of uLog in human-computer interaction studies.