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Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

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Characterizing eye gaze and mental workload for assistive device control.

Larisa Y C Loke^1,2, Demiana R Barsoum^1,2, Todd D Murphey¹

¹Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.

Wearable Technologies

|March 12, 2025

Summary

This study introduces a new method for eye gaze tracking, enabling continuous control of assistive devices. It differentiates between environmental scanning and interface operation, enhancing user interaction for individuals with motor impairments.

Keywords:

Assistive devices Characterization Control interfaces Eye gaze Workload

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Area of Science:

Human-Computer Interaction
Assistive Technology
Neuroscience

Background:

Eye gaze tracking is advancing, yet its application in assistive devices often remains limited to discrete control.
The full potential of continuous eye gaze signals for controlling assistive technology is largely untapped.
The 'Midas touch' problem hinders differentiating perceptual gaze from control-based gaze movements.

Purpose of the Study:

To develop and validate a method for collecting diverse eye gaze signals for individualized interface characterization.
To explore the integration of continuous eye gaze input into assistive device control.
To investigate the use of smooth pursuit characteristics for distinguishing gaze intent.

Main Methods:

Screen-based tasks were designed to isolate various eye movement types, collecting both reactionary and controlled gaze signals.
An individualized characterization of eye gaze interface use was developed based on collected data.
Smooth pursuit characteristics were utilized to differentiate between gaze for environmental scanning and interface operation.

Main Results:

A study with participants with motor impairments demonstrated the feasibility of continuous eye gaze input.
Individualized smooth pursuit metrics effectively differentiated between perceptual and operational gaze.
Eye gaze metrics for mental workload were explored, showing potential for real-time assessment.

Conclusions:

Continuous eye gaze control for assistive devices is feasible by differentiating gaze intent.
Individualized smooth pursuit analysis is key to overcoming the 'Midas touch' problem.
Eye tracking can serve as a sole input modality and for concurrent mental workload assessment in shared control systems.