Eye Movement as Indicators of Mental Workload to Trigger Adaptive Automation

Abstract

This research describes an approach to objective assessment of mental workload, by analyzing differences in pupil diameter and several aspects of eye movement (fixation time, saccade distance, and saccade speed) under different levels of mental workload. In an experiment, these aspects were measured by an eye-tracking device to examine whether these are indeed indicators for mental workload. Pupil diameter and fixation time both show a general significant increase if the mental workload increases while saccade distance and saccade speed do not show any significant differences. This assessment of mental workload could be a trigger for aiding the operator of an information system, in order to meet operational requirements.

Evaluation of head-free eye tracking as an input device for air traffic control

“…It is worth noticing that eye tracking could also bring clues on controller's objective internal state through pupil diameter (Causse et al 2012;de Greef et al 2009), saccadic activity (Ahlstrom and Friedman-Berg 2006) and eye blink measurements (Brookings, Wilson, and Swain 1996). This may help to adjust the controller's mental workload, for instance with an online adjustment of the number of aircraft to control.…”

What does germane load mean? An empirical contribution to the cognitive load theory

“…Pupillary response is one of the most extensively studied measures of cognitive load. Relationships between an increase in cognitive load and pupil diameter have been found in various contexts varying from such as simple cognitive tasks (Backs and Walrath, 1992 ; VanGerven et al, 2004 ) to naval simulators (De Greef et al, 2009 ); driving (Marshall, 2007 ); e-learning (Liu et al, 2011 ); e-shopping (DiStasi et al, 2011 ) and an AI web-based tool (Buettner, 2013 ). Unlike eye movement or blinking, the pupillary reflex is under control of the autonomous nervous system and cannot be voluntary controlled by the subject, which explains the enthusiasm among researchers for this type of measure.…”

Impact of Individual Differences on Reliance Optimization

“…In fact, research utilizing eye gaze behavior for adaptive automation is represented infrequently in the scientific literature and what has been conducted is almost exclusively focused on detection and mitigation of operator workload. However, this research is relevant in its demonstration that even relatively low level indices of eye gaze behavior such as pupil diameter (de Greef, Lafeber, van Oostendorp, & Lindenberg, 2009) and fixation dispersion (Fidopiastis et al, 2009) can successfully actuate adaptive automation, lending credence to the suggestion that it could be applied in the current context as well. In Study 3, eye fixation-based thresholds, determined from data collected in Study 2, are being applied for detection of changes in fatigue state that then trigger changes in surveillance task LOA.…”