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

Authors

Qian Chu, Jan-Gabriel Hartel, Alex Lepauvre, Lucia Melloni

Published in

Behavior research methods. Volume 58. Issue 8. Jun 29, 2026. Epub Jun 29, 2026.

Abstract

Mobile eye-tracking has revolutionized the study of human behavior and cognition by enabling researchers to record eye movements in the real world. However, the dynamic and multimodal nature of mobile eye-tracking data also introduces significant analytical challenges, including the alignment, integration, and interpretation of complex data. To fill these gaps, we present PyNeon, a versatile, community-oriented Python package designed to streamline the analysis of mobile eye-tracking, motion, and video data from the Neon eye-tracking system (Pupil Labs GmbH). We describe how PyNeon provides accessible APIs for reading, preprocessing, epoching, and exporting Neon data. Furthermore, it supports advanced video processing such as mapping between eye movement data and real-world coordinates and dynamic scanpath estimation. PyNeon presents an open-source and extendable framework for analyzing mobile eye-tracking data and forms the foundation for higher-level applications.

PMID:
42373975
Bibliographic data and abstract were imported from PubMed on 30 Jun 2026.

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