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Related Experiment Video

Updated: Jul 1, 2026

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

PyNeon: A Python package for the analysis of Neon multimodal mobile eye-tracking data.

Qian Chu1,2,3, Jan-Gabriel Hartel4, Alex Lepauvre4,5

  • 1Neural Circuits, Consciousness, and Cognition Research Group, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany. qian.chu@ae.mpg.de.

Behavior Research Methods
|June 29, 2026
PubMed
Summary
This summary is machine-generated.

PyNeon is a new Python package that simplifies analyzing mobile eye-tracking data. It addresses challenges in processing complex, real-world eye movement, motion, and video recordings.

Keywords:
BIDSEye movementsMobile eye-trackingOpen-source softwarePupil labs neonPython

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Area of Science:

  • Cognitive Science
  • Human-Computer Interaction
  • Neuroscience

Background:

  • Mobile eye-tracking enables real-world human behavior and cognition studies.
  • Analyzing dynamic, multimodal eye-tracking data presents significant challenges in alignment, integration, and interpretation.

Purpose of the Study:

  • Introduce PyNeon, a Python package to streamline mobile eye-tracking data analysis.
  • Provide accessible APIs for reading, preprocessing, epoching, and exporting Neon eye-tracking data.
  • Support advanced video processing, including real-world coordinate mapping and dynamic scanpath estimation.

Main Methods:

  • Developed PyNeon as a versatile, community-oriented Python package.
  • Implemented APIs for data handling and preprocessing.
  • Integrated advanced video processing capabilities for spatial and temporal analysis.

Main Results:

  • PyNeon offers streamlined analysis of mobile eye-tracking, motion, and video data.
  • The package facilitates mapping eye movements to real-world coordinates.
  • Dynamic scanpath estimation is supported for enhanced behavioral analysis.

Conclusions:

  • PyNeon provides an open-source, extendable framework for mobile eye-tracking data analysis.
  • The package simplifies complex data integration and interpretation.
  • PyNeon serves as a foundation for developing higher-level applications in behavioral research.