PupilEXT: Flexible Open-Source Platform for High-Resolution Pupillometry in Vision Research

Abstract

The human pupil behavior has gained increased attention due to the discovery of the intrinsically photosensitive retinal ganglion cells and the afferent pupil control path’s role as a biomarker for cognitive processes. Diameter changes in the range of 10–2 mm are of interest, requiring reliable and characterized measurement equipment to accurately detect neurocognitive effects on the pupil. Mostly commercial solutions are used as measurement devices in pupillometry which is associated with high investments. Moreover, commercial systems rely on closed software, restricting conclusions about the used pupil-tracking algorithms. Here, we developed an open-source pupillometry platform consisting of hardware and software competitive with high-end commercial stereo eye-tracking systems. Our goal was to make a professional remote pupil measurement pipeline for laboratory conditions accessible for everyone. This work’s core outcome is an integrated cross-platform (macOS, Windows and Linux) pupillometry software called PupilEXT, featuring a user-friendly graphical interface covering the relevant requirements of professional pupil response research. We offer a selection of six state-of-the-art open-source pupil detection algorithms (Starburst, Swirski, ExCuSe, ElSe, PuRe and PuReST) to perform the pupil measurement. A developed 120-fps pupillometry demo system was able to achieve a calibration accuracy of 0.003 mm and an averaged temporal pupil measurement detection accuracy of 0.0059 mm in stereo mode. The PupilEXT software has extended features in pupil detection, measurement validation, image acquisition, data acquisition, offline pupil measurement, camera calibration, stereo vision, data visualization and system independence, all combined in a single open-source interface, available at https://github.com/openPupil/Open-PupilEXT.

Measurement of Circadian Effectiveness in Lighting for Office Applications

“…As for example described by Kobbert [101] for the automotive context, the required data to develop this kind of statistical models can be obtained by combining in situ eyetracking [102] with state-of-the-art object recognition algorithms in order to determine characteristic gaze behavior distributions of office workers for a typical office day, e.g., like in the present case, with a focus on display work. The availability of such contextdependent eye-tracking based gaze behavior models does not only help to perform more reliable and meaningful estimates of the circadian effectiveness of the lit working environment adopting the novel measurement approach proposed in this work, but may also contribute to the optimization of the respective luminaires' light distributions to match the specific, task-related visual needs of the office workers [13].…”

Publication guidelines and recommendations for pupillary measurement in psychophysiological studies

“…Some software may be limited to specific data collection devices and/or platforms. Software acquisition of video data for pupillary assessment has been developed by Zandi et al (2021). Eye movement correction algorithms are presented by Gagl et al (2011; see also Geller et al, 2020) and by Hayes and Petrov (2016).…”

An Open Source Multi-Modal Data-Acquisition Platform for Experimental Investigation of Blended Control of Scale Vehicles

“…3. Using OpenCV [11] existing and bespoke open-source algorithms, our software outputs various time stamped data such as head and eye tracking, changes in blink frequency, yawn detection, pupil dilation, eye's widening, etc [12]. Such information can be employed to indicate changes in attention level [13].…”