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      • Experiment Design
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      • Eye Tracking
        • Presenting Stimuli in an Eye Tracking Task
        • How to Choose Eye Tracking Calibration Settings
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Eye Tracking Options in the Task Editor

Within a task, eye tracking is enabled and configured from the Settings button in the top-left corner of the task editor, under the Physiological Signals tab. From there you control how often the system recalibrates during the task, whether fixations are detected in addition to raw gaze, and which display mode gaze coordinates are measured in. Checking Enable Eye-Tracking: also offers to set up the common gaze and fixation recording events for you automatically, covering the typical case directly.

Two other capabilities live at the task level:

  • Recording gaze and fixation data as variables, via events built in the events editor, optionally restricted to specific stimulus objects rather than the whole frame.
  • Using SVG or Polygon shape objects as invisible masks to define areas of interest, so you can measure whether a participant looked at a specific region rather than just anywhere on the frame.

Learn More

Webcam Eye Tracking Guide

The Webcam Eye Tracking Guide is the complete reference for building an eye tracking study in Labvanced, covering stimuli, calibration settings, and everything summarized on this page in full detail. If you are new to eye tracking in Labvanced, it is the best place to start before diving into any single piece below.

Setting Up Eye Tracking in a Task

Setting Up Eye Tracking in a Task covers enabling and configuring eye tracking in full: the Settings button and Physiological Signals tab, recalibration and drift correction fields, Fixation Detection modes, and display mode choices. It is the detailed version of the overview given above.

Recording and Exporting Gaze Data

Recording and Exporting Gaze Data covers building the recording events in full: the automated event setup dialog, building gaze and fixation events manually, restricting recording to specific stimulus objects, and reading the resulting data export.

Using Shapes as Areas of Interest (AOI)

Using Shapes as Areas of Interest (AOI) covers the Polygon and SVG masking approach in full: how to draw an invisible mask that still registers gaze and fixation hits, and how to restrict a trigger to that mask so you can measure whether a participant looked at a specific stimulus rather than anywhere on the frame.

In-Lab Hardware Instead

If you are connecting your own in-lab eye tracking hardware rather than using Labvanced's webcam eye tracking, see Eye Tracking in Labvanced for that option.

Further Reading

Webcam Eye Tracking Accuracy and Study Design

The evidence behind webcam eye tracking's validated accuracy, and the design decisions that affect it.

Webcam Eye Tracking Technology

How Labvanced's webcam eye tracking technology works.

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Head Tracking in a Task