etformat: A Package for conversion and Analysis of EDF EyeTracker Data

Mohammad Ahsan Khodami
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Mohammad Ahsan Khodami: University of Padova

No gu4bd_v1, OSF Preprints from Center for Open Science

Abstract: Eye-tracking research provides critical insights into human cognition, attention, and behavior. However, handling raw EDF files remains challenging due to their complex structure and proprietary format. etformat is a Python package that simplifies EDF data extraction, conversion, and analysis, enabling researchers to process eye-tracking datasets efficiently. It supports EDF-to-CSV conversion, gaze path visualization, saccade analysis, calibration validation, and metadata extraction. By automating these processes, etformat enhances reproducibility, accelerates analysis workflows, and improves data accessibility across research domains, including psychology, neuroscience, usability testing, and human-computer interaction.

Date: 2025-03-06
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:gu4bd_v1

DOI: 10.31219/osf.io/gu4bd_v1

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