Measuring cognitive load of digital interface combining event-related potential and BubbleView

Area of Science:

• Human-Computer Interaction
• Neuroscience
• Aerospace Engineering

Background:

• Helmet-mounted display systems (HMDs) are critical for modern aircraft, necessitating effective interface design.
• Evaluating cognitive load in HMD users is essential for optimizing performance and safety.
• Existing methods for cognitive load assessment may lack comprehensiveness or objectivity.

Purpose of the Study:

• To propose and validate a novel method for measuring cognitive load in HMD interfaces.
• To combine electroencephalography-based event-related potentials (ERPs) with eye-tracking-based BubbleView.
• To provide a more objective and reliable evaluation of HMD interface design.

Main Methods:

• Subjects interacted with different HMD interfaces while their cognitive load was measured.
• Event-related potentials (ERPs), specifically P3b and P2 components, were analyzed to assess attention input.
• BubbleView data was analyzed to understand the distribution of subjects' attention resources.

Main Results:

• HMD interfaces with symmetrical and simple layouts resulted in lower cognitive load.
• Subjects predominantly directed their attention towards the upper regions of the HMD interface.
• The combined ERP and BubbleView approach yielded comprehensive and reliable HMD interface evaluation data.

Conclusions:

• A combined ERP and BubbleView methodology offers a robust approach for HMD interface evaluation.
• Interface design principles such as symmetry and simplicity are crucial for reducing cognitive load.
• This method supports iterative design and optimization of digital interfaces for HMDs.