Related Experiment Video
Updated: Jul 3, 2026

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Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior
Published on: November 14, 2018
Behaviour and gaze analyses during a goal-directed locomotor task.
Michael E Cinelli1, Aftab E Patla, Fran Allard
1Department of Cognitive & Linguistic Science, Brown University, Providence, RI 02912, USA. Michael_Cinelli@brown.edu
Summary
Participants used perception-action coupling to navigate moving doors, adjusting walking speed and gaze for successful passage. Vision played a key role, with longer processing times for unpredictable door movements.
Area of Science:
- Human locomotion
- Perception-action coupling
- Visual control of movement
Background:
- Understanding how humans control locomotion in dynamic environments is crucial for designing safe and efficient spaces.
- Perception-action coupling, the continuous interaction between perceiving and acting, is hypothesized to be a key mechanism.
Purpose of the Study:
- To investigate if perception-action coupling governs behavior when walking through moving doors.
- To determine the specific contribution of visual information to this behavior.
Main Methods:
- Six participants walked towards motor-driven doors moving symmetrically or asymmetrically (20-40 cm/s).
- Walking velocity, velocity variability, and gaze behavior (fixation duration and patterns) were recorded.
- Success rates of passing through the aperture were measured.
Main Results:
- Participants successfully controlled approach velocity by slowing down, increasing velocity variability, and maintaining high success rates.
- Fixation durations were longer for asymmetrical door movements, indicating increased visual processing demands.
- Gaze primarily focused on doors initially, shifting to the aperture in the final phase, with ~60% of time fixating environmental objects.
Conclusions:
- Perception-action coupling is utilized to control locomotion and steer through dynamic apertures.
- Visual information is critical for navigating moving obstacles, with processing demands varying based on predictability.

