Using Pupillometry to Indicate the Cognitive Redline. Carolina Rodriguez-Paras, Shiyan Yang, & Thomas K. Ferris. Texas A&M University. Physiological ...
Proceedings of the Human Factors and Ergonomics Society 2016 Annual Meeting
685
Using Pupillometry to Indicate the Cognitive Redline Carolina Rodriguez-Paras, Shiyan Yang, & Thomas K. Ferris Texas A&M University Physiological measures, which are influenced by the arousal of the autonomous nervous system, have been studied as indicators of extreme levels of mental workload that approach or exceed the cognitive “redline”, the point at which task demand exceeds the supply of cognitive resources. In response to increasing task demands, measures such as heart rate variability show asymptotic patterns in arousal that are consistent with plateau patterns in subjective self-reported measures. This suggests potential to use physiological indicators in real time to predict when an operator is at increased risk of cognitive overload. Expanding on prior work, the current study examined pupil diameter as a new potential indicator of the cognitive redline in a multitask environment created with the Multi-Attribute Task Battery-II (MATB-II). Results showed that pupil diameter is sensitive to imposed mental workload and exhibits a similar asymptotic pattern that may provide another potential real-time indicator of the cognitive redline.
Copyright 2016 by Human Factors and Ergonomics Society. DOI 10.1177/1541931213601157
SUMMARY The cognitive redline represents an extreme condition of mental workload which may be thought of as the point when external task demands approach the limit of what internal mental resources can provide to satisfy these demands (Wickens, 2008; Wickens, Hollands, Parasuraman, & Banbury, 2012). It represents the threshold at which humans experience an overloaded mental state (Grier, Wickens, Kaber, Strayer, Boehm-Davis, Trafton, & John, 2008; Wickens, 2008). The cognitive redline has traditionally been identified by characteristic performance patterns when approaching an operator’s cognitive capacity (Wickens, 2008; Wickens, et al., 2012). But is not always practical to rely on these measures for the early detection and prevention of problems associated with overload. Recent efforts have focused on identifying “plateau” patterns in subjective and physiological measures of cognitive load. In particular, heart rate variability (HRV) measures show plateau patterns that are consistent with performance degradation (Rodriguez Paras, Yang, Tippey, & Ferris, 2015). However, HRV is more reliable as an indicator of the cognitive redline over longer time windows and may not have sufficient predictive power over shorter time windows. Another physiological indicator, pupil diameter, has a faster response and can serve as an effective indicator of mental workload (Beatty, 1982). The current study investigated pupillometry as a real-time indicator of the cognitive redline of workload. A multitasking scenario was created by using the Multi-Attribute Task Battery– II (MATB-II) with five distinct levels of imposed task load. A total of 10 participants (average age 25.3 years; 4 males and 6 females) were recruited. Physiological data collected included galvanic skin response, electrooculography, and pupil diameter measured using the “Pupil” hardware by Pupil Labs (Kassner, Patera, & Bulling, 2014). Only pupillometry data are reported. Subjective measures included the Short Stress State Questionnaire (SSSQ), Workload Profile Index (WPI), and NASA-Task Load Index (NASA-TLX). Pupil dilation, analyzed in RStudio using a 95% confidence interval, shows that the workload level significantly affects pupil size (F(4, 35) = 3.185, p = 0.023), showing an apparently linear increase over moderate ranges of difficulty, and plateaus at the three highest levels of imposed task load. Gender as a factor was significant (p < 0.001).
Task load also significantly impacted NASA-TLX measures (F (4,36) = 18.25, p
