PeyeMMV: Python implementation of EyeMMV’s fixation detection algorithm

• Published in: Software impacts Vol. 15; p. 100475
• Main Author: Krassanakis, Vassilios
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2023
• Subjects: Dispersion-based algorithms; Eye movements; EyeMMV toolbox; Fixation detection; LandRate toolbox; Python; EyeMMV toolbox; Eye movements; Fixation detection; LandRate toolbox; Dispersion-based algorithms; Python
• ISSN: 2665-9638; 2665-9638
• DOI: 10.1016/j.simpa.2023.100475

This article presents a new Python module called PeyeMMV. The module implements the two-step spatial dispersion fixation detection algorithm imported in both EyeMMV and LandRate MATLAB toolboxes. This algorithm is based on spatiotemporal criteria, belongs to the family of I-DT based algorithms and can be used as a spatial noise filtering approach during fixation identification process. PeyeMMV module could be utilized in order to extract fixation clusters among raw gaze data as well as to generate a basic plot that visualizes both gaze data and fixation centers positions. The module could be easily imported in every Python script or module. •PeyeMMV is a Python module that can be used to extract fixation clusters among raw gaze data.•Its core fixation detection algorithm belongs to the family of the I-DT based algorithms.•It implements the two-step spatial dispersion fixation detection algorithm imported in both EyeMMV and LandRate MATLAB toolboxes.•It can be used as a spatial noise filter during fixation identification.•It can be utilized to generate a basic plot that visualizes both gaze data and fixation centers positions.