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

作者：Qian Chu, Jan-Gabriel Hartel, Alex Lepauvre, Lucía Melloni · 发表于：Behavior Research Methods · 年份：2026 · DOI：10.3758/s13428-026-03089-8 · 研究领域：Gaze Tracking and Assistive Technology

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.