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Physiological metrics of mental workload: A review of recent progress
Published in Diane L. Damos, Multiple-task performance, 2020
The intrusiveness of the pupillary measure depends on the methodological requirements of the techniques employed during recording. Two optical techniques, photographic pupillometry and electronic video-based pupillometry, have been used in recent years. Photographic pupillometry, the simpler and less expensive of the two techniques, involves photographing changes in the pupil during task performance. The pupil is usually photographed every 0.5 to 1 second and the changes are quantified by measuring the diameter of the image of the pupil with an ordinary ruler. As might be expected, such a technique is quite time-consuming when large numbers of subjects and experimental conditions are involved. This technique also requires that the head remain relatively stable during data collection (a chin rest and a bite bar are usually employed).
Attention and the Assessment of Mental Workload
Published in Robert W. Proctor, Van Zandt Trisha, Human Factors in Simple and Complex Systems, 2018
Robert W. Proctor, Van Zandt Trisha
Many kinds of psychophysiological measures have been used to measure workload, but they all generally fall into two classes: those that measure general arousal and those that measure brain activity. General arousal level is presumed to increase as mental workload increases, and indices of arousal thus provide single measures of workload. One such technique is pupillometry, or the measurement of pupil diameter (Sirois & Brisson, 2014). Pupil diameter provides an indicator of the amount of attentional resources that are expended to perform a task (Beatty, 1982; Kahneman, 1973). The greater the workload demands, the larger the pupil size. The changes that occur are small but reliable, and require a pupillometer to allow sufficiently sensitive measurements. While useful as a general measure of workload, pupil diameter cannot distinguish between the different resources that are being overloaded in the performance of a task.
Biometrically Measured Affect for Screen-Based Drone Pilot Skill Acquisition
Published in International Journal of Human–Computer Interaction, 2023
Fatemeh Dalilian, David Nembhard
Eye-tracking technologies have been effectively used for studying complex task learning (Fletcher et al., 2017; Krejtz et al., 2018). Several measurements of visual behavior including dwells, blink durations, blink rates, pupil diameters, and eye closure times have been shown to be useful in aviation research (Peißl et al., 2018). Among eye tracking metrics, pupillary response was selected to reflect information processing demands in beyond direct physical metrics (Backs & Walrath, 1992). Pupillometry has gained considerable attention as an objective measure of affect related to cognitive features, underlying skill learning, dynamic decision-making, expert vs. novice behavior, multitasking, and complex task performance (Peysakhovich et al., 2015; Qiao et al., 2022; Tichon et al., 2014). A review study by van der Wel and van Steenbergen (2018) supported that pupil dilation reflects effort exerted in response to increased cognitive demand during cognitive control tasks. Thus, greater task demands are associated with greater pupil dilation and once task demands exceed individual cognitive capacity, pupil dilation tends not to increase further.
Bodies in mind: using peripheral psychophysiology to probe emotional and social processes
Published in Journal of the Royal Society of New Zealand, 2021
Gina M. Grimshaw, Michael C. Philipp
The pupil is the opening in the eye through which light passes to the retina. The size of the pupil is controlled by two sets of muscles in the iris. Contraction of the sphincter muscle (under parasympathetic control) constricts the pupil, while contraction of the dilator muscle (under sympathetic control) widens it (see Wang and Munoz 2015, for further review of pupil physiology). Changes in pupil diameter affect vision: constricted pupils are optimised for visual acuity (i.e. sharp visual focus) whereas dilated pupils are optimised for visual sensitivity (i.e. detection of faint stimuli). The parasympathetic pathway mediates the light reflex, a rapid constriction of the pupil that occurs when light levels suddenly increase. The sympathetic pathway, in contrast, acts more slowly to dilate the pupil when people engage with important, interesting, or emotional stimuli (Hess and Polt 1964; Bradley et al. 2008). This pathway is under control of the locus coeruleus, a neural structure that plays an important role in alertness and waking via modulation of norepinephrine (Aston-Jones and Cohen 2005). In different experimental contexts, pupil dilation can be a physiological outcome of both cognitive effort (Kahneman and Beatty 1966; Einhauser 2017) and emotional arousal (Hess and Polt 1964; Bradley et al. 2008). Relative changes in pupil dilation can be measured with most eye-trackers, meaning that pupillometry can be easily integrated into lab-based experiments of visual perception (Sirois and Brisson 2014; Mathôt 2018).
Detecting Intention Through Motor-Imagery-Triggered Pupil Dilations
Published in Human–Computer Interaction, 2019
David Rozado, Martin Lochner, Ulrich Engelke, Andreas Dünser
The breadth of conditions that can be detected using pupillometry warrants an overview of what this signal is and why it behaves as an index to so many mental events or processes. First, it is important to understand that the term pupillometry refers to what we call second-order dilations of the pupil, of around 0.5 mm on average (e.g., Laeng & Sulutvedt, 2014). By comparison, first-order dilations of the pupil occur with changes in ambient lighting, stimulus brightness, metabolism and certain medications, and range from 2 mm to 8 mm on average (Watson & Yellott, 2012), and they have been shown to interact with the effects of cognitive load (Kun, Palinko, & Razumenić, 2012). Obviously, then, the measurement of cognitively meaningful pupil dilations requires the careful control of lighting conditions, stimulus brightness, and other applicable factors such as exercise and medication.