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Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System
Published on: March 17, 2023
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OWLET: An automated, open-source method for infant gaze tracking using smartphone and webcam recordings
Denise M Werchan1,2, Moriah E Thomason3,4, Natalie H Brito5
1Department of Population Health, New York University School of Medicine, 227 E 30th St, 7th Fl, New York, NY, 10016, USA. denise.werchan@nyulangone.org.
Behavior Research Methods
|September 7, 2022
Summary
Researchers developed a new method to track infant eye movements using webcams, enabling large-scale studies on infant cognition from home. This advances understanding of early cognitive development and diverse populations.
Area of Science:
- Developmental Psychology
- Cognitive Science
- Computer Vision
Background:
- Infant cognition research traditionally relies on constrained in-lab eye-tracking.
- This limits data collection scale and diversity across socioeconomic and cultural backgrounds.
- Preverbal infants cannot verbally report their thought processes, necessitating observational methods like eye tracking.
Purpose of the Study:
- To introduce a novel, open-source methodology for analyzing infant eye-tracking data collected remotely in the home.
- To enable large-scale, diverse data collection on infant cognitive processes.
- To validate a new tool for robust estimation of infant gaze from personal device recordings.
Main Methods:
- Developed an online webcam-linked eye tracker (OWLET) using computer vision, machine learning, and ecological psychology algorithms.
- Collected and analyzed infant eye-tracking data remotely using personal devices (smartphones, webcams).
- Validated OWLET with 127 seven-month-old infants using a visual attention task and parental-report measures.
Main Results:
- OWLET reliably estimates infants' point of gaze across various devices and home contexts.
- The method demonstrated excellent external validity when compared with parental-report measures of attention.
- Successful remote validation in a large sample of infants indicates robustness and scalability.
Conclusions:
- The OWLET platform significantly enhances the ability to conduct rapid, large-scale assessments of infant cognitive processes.
- Remote eye-tracking addresses critical needs for diversity and accessibility in human developmental studies.
- This advance supports ecological validity in behavioral research and broadens psychological science insights.
