Optimizing Waveform Descriptors and Pupillometry of the Pupillary Light Reflex Using Data Acquired from Video-Based Eye Trackers

摘要

Previous models of the pupillary light reflex (PLR) provided a compelling narrative to the complex dynamics of pupiloscillations. However, simple descriptors, such as the time constant obtained from curve fits of a single exponential decay, canprovide easily interpretable insights into the dynamics of the PLR. To optimize these time constant estimates and improve theoverall quality of the pupillometric data, the ideal eye-tracking system should implement pupillary curve-fitted algorithms thatare robust against occlusion artifacts and provide the most accurate centroid approximation.