New Interface To Cope With Unreliable Airspeed Indications: A Behavioral And Eye-Tracking Study.

2021 ◽  
Author(s):  
Eve Fabre ◽  
Patrick Braca ◽  
Vsevolod Peysakhovich ◽  
Frédéric Dehais
Keyword(s):  
Eye Tracking ◽  
Efficient Solution ◽  
Mental Workload ◽  
Flight Deck ◽  
Monitoring Performance

When unreliable airspeed events occur, the pilot flying (PF) is required to fly the aircraft using the thrust and the pitch parameters that are displayed in two distanced locations of the flight deck. The Sycopaero interface was designed to limit the PF’s workload by automatically displaying thrust and pitch values specific to aircraft configuration on the Primary Flight Display. Participants performed a simulated flight scenario in which they lost airspeed information during take-off with and without the Sycopaero interface. Both behavioral and ocular results demonstrate that the Sycopaero interface significantly lowers PFs’ mental workload and improves their monitoring performance. Taken together, these results suggest that the Sycopaero interface may be an efficient solution in case of unreliable airspeed events.

Investigating the Use of Two Low Cost Eye Tracking Systems for Detecting Pupillary Response to Changes in Mental Workload

2016 ◽  
Vol 60 (1) ◽  
pp. 37-41 ◽  
Author(s):  
Joseph Coyne ◽  
Ciara Sibley
Keyword(s):  
Eye Tracking ◽  
Pupil Size ◽  
Mental Workload ◽  
Low Cost ◽  
Digit Span ◽  
Pupillary Response ◽  
Background Luminance ◽  
Tracking Systems ◽  
Lighting Conditions ◽  
Size Data

Eye tracking technologies are being utilized at increasing rates within industry and research due to the very recent availability of low cost systems. This paper presents results from a study assessing two eye tracking systems, Gazepoint GP3 and Eye Tribe, both of which are available for under $500 and provide streaming gaze and pupil size data. The emphasis of this research was in evaluating the ability of these eye trackers to identify changes in pupil size which occur as a function of variations in lighting conditions as well as those associated with workload. Ten volunteers participated in an experiment in which a digit span task was employed to manipulate workload as user’s fixated on a monitor which varied in background luminance (black, gray and white). Results revealed that both systems were able to significantly differentiate pupil size differences in high and low workload trials and changes due to the monitor’s luminance. These findings are exceedingly promising for human factors researchers, as they open up the opportunity to augment studies with non-obtrusive, streaming measures of mental workload with technologies available for as little as $100.

scholarly journals Comparison of the Effects of Automated and Manual Record Keeping on Anesthetists’ Monitoring Performance: Randomized Controlled Simulation Study

10.2196/16036 ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. e16036
Author(s):  
Man-Kei Tse ◽  
Simon Y W Li ◽  
Tsz Hin Chiu ◽  
Chung Wai Lau ◽  
Ka Man Lam ◽  
...  
Keyword(s):  
Situation Awareness ◽  
Simulation Study ◽  
Mental Workload ◽  
Detection Accuracy ◽  
High Fidelity ◽  
High Fidelity Simulation ◽  
Record Keeping ◽  
Randomized Controlled ◽  
Monitoring Performance ◽  
Manual Record

Background Anesthesia information management systems (AIMSs) automatically import real-time vital signs from physiological monitors to anesthetic records, replacing part of anesthetists’ traditional manual record keeping. However, only a handful of studies have examined the effects of AIMSs on anesthetists’ monitoring performance. Objective This study aimed to compare the effects of AIMS use and manual record keeping on anesthetists’ monitoring performance, using a full-scale high-fidelity simulation. Methods This simulation study was a randomized controlled trial with a parallel group design that compared the effects of two record-keeping methods (AIMS vs manual) on anesthetists’ monitoring performance. Twenty anesthetists at a tertiary hospital in Hong Kong were randomly assigned to either the AIMS or manual condition, and they participated in a 45-minute scenario in a high-fidelity simulation environment. Participants took over a case involving general anesthesia for below-knee amputation surgery and performed record keeping. The three primary outcomes were participants’ (1) vigilance detection accuracy (%), (2) situation awareness accuracy (%), and (3) subjective mental workload (0-100). Results With regard to the primary outcomes, there was no significant difference in participants’ vigilance detection accuracy (AIMS, 56.7% vs manual, 56.7%; P=.50), and subjective mental workload was significantly lower in the AIMS condition than in the manual condition (AIMS, 34.2 vs manual, 46.7; P=.02). However, the result for situation awareness accuracy was inconclusive as the study did not have enough power to detect a difference between the two conditions. Conclusions Our findings suggest that it is promising for AIMS use to become a mainstay of anesthesia record keeping. AIMSs are effective in reducing anesthetists’ workload and improving the quality of their anesthetic record keeping, without compromising vigilance.

scholarly journals Effects of Workload and Workload Transitions on Attention Allocation in a Dual-Task Environment: Evidence From Eye Tracking Metrics

2020 ◽  
Vol 14 (2) ◽  
pp. 132-151
Author(s):  
Nadine Marie Moacdieh ◽  
Shannon P. Devlin ◽  
Hussein Jundi ◽  
Sara Lu Riggs
Keyword(s):  
Eye Tracking ◽  
Dual Task ◽  
Secondary Task ◽  
High Performance ◽  
Mental Workload ◽  
Attention Allocation ◽  
Task Load ◽  
Significant Difference ◽  
High Workload ◽  
And Control

High mental workload, in addition to changes in workload, can negatively affect operators, but it is not clear how sudden versus gradual workload transitions influence performance and visual attention allocation. This knowledge is important as sudden shifts in workload are common in multitasking domains. The objective of this study was to investigate, using performance and eye tracking metrics, how constant versus variable levels of workload affect operators in the context of a dual-task paradigm. An unmanned aerial vehicle command and control simulation varied task load between low, high, gradually transitioning from low to high, and suddenly transitioning from low to high. Performance on a primary and secondary task and several eye tracking measures were calculated. There was no significant difference between sudden and gradual workload transitions in terms of performance or attention allocation overall; however, both sudden and gradual workload transitions changed participants’ strategy in dealing with the primary and secondary task as compared to low/high workload. Also, eye tracking metrics that are not frequently used, such as transition rate and stationary entropy, provided more insight into performance differences. These metrics can potentially be used to better understand operators’ strategies and could form the basis of an adaptive display.

scholarly journals A Simple(r) Tool For Examining Fixations

2016 ◽  
Vol 9 (4) ◽  
Author(s):  
Francesco Di Nocera ◽  
Claudio Capobianco ◽  
Simon Mastrangelo
Keyword(s):  
Eye Tracking ◽  
Open Source ◽  
Open Source Software ◽  
Time Course ◽  
Nearest Neighbor ◽  
Mental Workload ◽  
Short Paper ◽  
Tracking Data ◽  
Mental Load ◽  
Simple Tool

This short paper describes an update of A Simple Tool For Examining Fixations (ASTEF) developed for facilitating the examination of eye-tracking data and for computing a spatial statistics algorithm that has been validated as a measure of mental workload (namely, the Nearest Neighbor Index: NNI). The code is based on Matlab® 2013a and is currently distributed on the web as an open-source project. This implementation of ASTEF got rid of many functionalities included in the previous version that are not needed anymore considering the large availability of commercial and open-source software solutions for eye-tracking. That makes it very easy to compute the NNI on eye-tracking data without the hassle of learning complicated tools. The software also features an export function for creating the time series of the NNI values computed on each minute of the recording. This feature is crucial given that the spatial distribution of fixations must be used to test hypotheses about the time course of mental load.

scholarly journals Multimodal Study of the Effects of Varying Task Load Utilizing EEG, GSR and Eye-Tracking

2019 ◽  
Author(s):  
Jannis Born ◽  
Babu Ram Naidu Ramachandran ◽  
Sandra Alejandra Romero Pinto ◽  
Stefan Winkler ◽  
Rama Ratnam
Keyword(s):  
Eye Tracking ◽  
Task Performance ◽  
Mental Workload ◽  
Cognitive Task ◽  
Physiological Data ◽  
Postal Code ◽  
Subjective Data ◽  
Task Load ◽  
Minimum Number ◽  
Participant Response

AbstractObjectiveThe effect of task load on performance is investigated by simultaneously collecting multi-modal physiological data and participant response data. Periodic response to a questionnaire is also obtained. The goal is to determine combinations of modalities that best serve as predictors of task performance.ApproachA group of participants performed a computer-based visual search task mimicking postal code sorting. A five-digit number had to be assigned to one of six different non-overlapping numeric ranges. Trials were presented in blocks of progressively increasing task difficulty. The participants’ responses were collected simultaneously with 32 channels of electroencephalography (EEG) data, eye-tracking data, and Galvanic Skin Response (GSR) data. The NASA Task-Load-Index self-reporting instrument was administered at discrete time points in the experiment.Main resultsLow beta frequency EEG waves (12.5-18 Hz) were more prominent as cognitive task load increased, with most activity in frontal and parietal regions. These were accompanied by more frequent eye blinks and increased pupillary dilation. Blink duration correlated strongly with task performance. Phasic components of the GSR signal were related to cognitive workload, whereas tonic components indicated a more general state of arousal. Subjective data (NASA TLX) as reported by the participants showed an increase in frustration and mental workload. Based on one-way ANOVA, EEG and GSR provided the most reliable correlation to perceived workload level and were the most informative measures (taken together) for performance prediction.SignificanceNumerous modalities come into play during task-related activity. Many of these modalities can provide information on task performance when appropriately grouped. This study suggests that while EEG is a good predictor of task performance, additional modalities such as GSR increase the likelihood of more accurate predictions. Further, in controlled laboratory conditions, the most informative or minimum number of modalities can be isolated for monitoring in real work environments.

Sign in / Sign up

Export Citation Format

Share Document