Eye Tracking
Eye tracking is a non-invasive method for measuring where people look, how their gaze moves, and how visual attention shifts over time. It captures data such as gaze position, fixations, saccades, and pupil size, offering insight into cognitive processes, attention, and visual search behaviour.
How Eye Tracking Works
Eye trackers estimate gaze by monitoring the position of the eye relative to the screen or environment. Most modern systems use infrared illumination and one or more cameras to detect key features of the eye:
- the pupil
- corneal reflections created by infrared light
By analysing the geometric relationship between these features, the system calculates the user’s point of regard on a screen or within a 3D environment.
Common eye tracking setups include:
- remote eye trackers placed below a monitor
- screen-mounted or laptop-integrated devices
- wearable glasses for mobile and naturalistic studies
- VR/AR headsets with built-in tracking modules
Types of Measurements
Eye tracking produces several core metrics:
- Fixations: periods when the gaze is relatively stable
- Saccades: fast ballistic eye movements between fixations
- Scanpaths: sequences of fixations and saccades
- Pupil diameter: changes in pupil size related to cognitive load, arousal, or lighting
- Blink rate: an indicator of fatigue or engagement
These metrics can be used individually or combined to analyse task performance and behaviour.
Data Quality and Calibration
Most systems require a short calibration step to map eye features to screen coordinates. Data quality depends on:
- lighting conditions
- camera resolution
- head movement
- glasses or contact lenses
- angle between the user’s face and the sensor
Wearable and VR-based systems typically tolerate more motion but may have narrower tracking ranges.
Strengths and Limitations
Strengths include:
- high temporal resolution (60–1000 Hz depending on hardware)
- direct access to visual attention patterns
- suitability for visual search, reading, and interface design studies
- usability in both controlled and naturalistic environments
Limitations include:
- sensitivity to lighting and head pose
- calibration drift over time
- reduced performance with certain eyewear
- inability to directly infer cognition without contextual information
Eye tracking does not reveal why a user looks at something by itself; interpretation requires task context and supporting data.
Applications in HCI and Neuroergonomics
Eye tracking is used across many areas, including:
- evaluating user interfaces and visual layouts
- studying attention and visual search strategies
- analysing reading behaviour
- assessing workload via pupil diameter
- adaptive systems that respond to gaze patterns
- mobile and VR interaction research
