scholarly journals Eye movement planning on Single-Sensor-Single-Indicator displays is vulnerable to user anxiety and cognitive load

2017 ◽  
Vol 10 (5) ◽  
Author(s):  
Jonathan Allsop ◽  
Rob Gray ◽  
Heinrich Bülthoff ◽  
Lewis Chuang
Keyword(s):  
Cognitive Load ◽  
Task Performance ◽  
Eye Movement ◽  
Movement Planning ◽  
Data Visualisation ◽  
Gaze Behavior ◽  
Single Indicator ◽  
Single Sensor ◽  
Indicator Data ◽  
Back Task

In this study, we demonstrate the effects of anxiety and cognitive load on eye movement planning in an instrument flight task adhering to a single-sensor-single-indicator data visualisation design philosophy. The task was performed in neutral and anxiety conditions, while a low or high cognitive load, auditory n-back task was also performed. Cognitive load led to a reduction in the number of transitions between instruments, and impaired task performance. Changes in self-reported anxiety between the neutral and anxiety conditions positively correlated with changes in the randomness of eye movements between instruments, but only when cognitive load was high. Taken together, the results suggest that both cognitive load and anxiety impact gaze behavior, and that these effects should be explored when designing data visualization displays.

scholarly journals Eye Movements in Response to Pain-Related Feelings in the Presence of Low and High Cognitive Loads

2020 ◽  
Vol 10 (5) ◽  
pp. 92
Author(s):  
Ramtin Zargari Marandi ◽  
Camilla Ann Fjelsted ◽  
Iris Hrustanovic ◽  
Rikke Dan Olesen ◽  
Parisa Gazerani
Keyword(s):  
Eye Movements ◽  
Cognitive Load ◽  
Eye Movement ◽  
Cognitive Processing ◽  
Pain Perception ◽  
Cognitive Task ◽  
Load Level ◽  
Task Load ◽  
Pupillary Responses ◽  
Movement Characteristics

The affective dimension of pain contributes to pain perception. Cognitive load may influence pain-related feelings. Eye tracking has proven useful for detecting cognitive load effects objectively by using relevant eye movement characteristics. In this study, we investigated whether eye movement characteristics differ in response to pain-related feelings in the presence of low and high cognitive loads. A set of validated, control, and pain-related sounds were applied to provoke pain-related feelings. Twelve healthy young participants (six females) performed a cognitive task at two load levels, once with the control and once with pain-related sounds in a randomized order. During the tasks, eye movements and task performance were recorded. Afterwards, the participants were asked to fill out questionnaires on their pain perception in response to the applied cognitive loads. Our findings indicate that an increased cognitive load was associated with a decreased saccade peak velocity, saccade frequency, and fixation frequency, as well as an increased fixation duration and pupil dilation range. Among the oculometrics, pain-related feelings were reflected only in the pupillary responses to a low cognitive load. The performance and perceived cognitive load decreased and increased, respectively, with the task load level and were not influenced by the pain-related sounds. Pain-related feelings were lower when performing the task compared with when no task was being performed in an independent group of participants. This might be due to the cognitive engagement during the task. This study demonstrated that cognitive processing could moderate the feelings associated with pain perception.

scholarly journals The role of cognitive load in modulating social looking: a mobile eye tracking study

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Laura J. Bianchi ◽  
Alan Kingstone ◽  
Evan F. Risko
Keyword(s):  
Cognitive Load ◽  
Load Condition ◽  
Social Situation ◽  
Lower Proportion ◽  
Eye Tracker ◽  
Attentional Resources ◽  
Subject Design ◽  
Video Experiment ◽  
Back Task

Abstract The effect of cognitive load on social attention was examined across three experiments in a live pedestrian passing scenario (Experiments 1 and 2) and with the same scenario presented as a video (Experiment 3). In all three experiments, the load was manipulated using an auditory 2-back task. While the participant was wearing a mobile eye-tracker, the participant’s fixation behavior toward a confederate was recorded and analyzed based on temporal proximity from the confederate (near or far) and the specific regions of the confederate being observed (i.e., head or body). In Experiment 1 we demonstrated an effect of cognitive load such that there was a lower proportion of fixations and time spent fixating toward the confederate in the load condition. A similar pattern of results was found in Experiment 2 when a within-subject design was used. In Experiment 3, which employed a less authentic social situation (i.e., video), a similar effect of cognitive load was observed. Collectively, these results suggest attentional resources play a central role in social attentional behaviors in both authentic (real-world) and less authentic (video recorded) situations.

scholarly journals Saliency-Based Gaze Visualization for Eye Movement Analysis

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5178
Author(s):  
Sangbong Yoo ◽  
Seongmin Jeong ◽  
Seokyeon Kim ◽  
Yun Jang
Keyword(s):  
Eye Movements ◽  
Visual Attention ◽  
Eye Movement ◽  
Visual Stimuli ◽  
Saliency Map ◽  
Gaze Behavior ◽  
The Gaze ◽  
Movement Data ◽  
Visual Clues ◽  
Human Visual Attention

Gaze movement and visual stimuli have been utilized to analyze human visual attention intuitively. Gaze behavior studies mainly show statistical analyses of eye movements and human visual attention. During these analyses, eye movement data and the saliency map are presented to the analysts as separate views or merged views. However, the analysts become frustrated when they need to memorize all of the separate views or when the eye movements obscure the saliency map in the merged views. Therefore, it is not easy to analyze how visual stimuli affect gaze movements since existing techniques focus excessively on the eye movement data. In this paper, we propose a novel visualization technique for analyzing gaze behavior using saliency features as visual clues to express the visual attention of an observer. The visual clues that represent visual attention are analyzed to reveal which saliency features are prominent for the visual stimulus analysis. We visualize the gaze data with the saliency features to interpret the visual attention. We analyze the gaze behavior with the proposed visualization to evaluate that our approach to embedding saliency features within the visualization supports us to understand the visual attention of an observer.

scholarly journals Study on cognitive load of OM interface and eye movement experiment for nuclear power system

2020 ◽  
Vol 52 (1) ◽  
pp. 78-86
Author(s):  
Jingling Zhang ◽  
Daizhong Su ◽  
Yan Zhuang ◽  
Furong QIU
Keyword(s):  
Power System ◽  
Cognitive Load ◽  
Eye Movement ◽  
Nuclear Power ◽  
Nuclear Power System

Determining Gaze Behavior Patterns in On-Screen Testing

2020 ◽  
pp. 073563312097861
Author(s):  
Marko Pejić ◽  
Goran Savić ◽  
Milan Segedinac
Keyword(s):  
Eye Tracking ◽  
Eye Movement ◽  
Undergraduate Students ◽  
Behavior Pattern ◽  
Machine Learning Techniques ◽  
Software System ◽  
Gaze Behavior ◽  
Gaze Patterns ◽  
Presentation Methods ◽  
Tracking Device

This study proposes a software system for determining gaze patterns in on-screen testing. The system applies machine learning techniques to eye-movement data obtained from an eye-tracking device to categorize students according to their gaze behavior pattern while solving an on-screen test. These patterns are determined by converting eye movement coordinates into a sequence of regions of interest. The proposed software system extracts features from the sequence and performs clustering that groups students by their gaze pattern. To determine gaze patterns, the system contains components for communicating with an eye-tracking device, collecting and preprocessing students’ gaze data, and visualizing data using different presentation methods. This study presents a methodology to determine gaze patterns and the implementation details of the proposed software. The research was evaluated by determining the gaze patterns of 51 undergraduate students who took a general knowledge test containing 20 questions. This study aims to provide a software infrastructure that can use students’ gaze patterns as an additional indicator of their reading behaviors and their processing attention or difficulty, among other factors.

scholarly journals Cognitive task performance under (combined) conditions of a metabolic and sensory stressor

2020 ◽  
Author(s):  
Charelle Bottenheft ◽  
Anne-Marie Brouwer ◽  
Ivo Stuldreher ◽  
Eric Groen ◽  
Jan van Erp
Keyword(s):  
Task Performance ◽  
Electrodermal Activity ◽  
Cognitive Task ◽  
Lower State ◽  
Subjective Data ◽  
Breakfast Skipping ◽  
Cognitive Task Performance ◽  
Underlying Mechanisms ◽  
Skipping Breakfast ◽  
Back Task

AbstractEffects of stressors on cognitive task performance have primarily been studied in isolation, and little is known about the combined effects of two or more stressors. This study examined how a metabolic stressor (skipping breakfast) and a sensory stressor (noise) affect cognitive task performance in isolation and combined. In addition to performance, we collected physiological and subjective data to get insight in the underlying mechanisms. Twenty participants came to the lab twice, once after skipping breakfast, and once after a standardized breakfast. They performed runs of the 2-back task and the International Shopping List Task, which were alternately presented with and without noise. During the 2-back task, electrocardiography (ECG), electrodermal activity (EDA), and electroencephalography (EEG) were recorded. Subjective ratings on effort and stress were also collected. No interaction effects between the two stressors on cognitive performance were found. Skipping breakfast did not cause hypoglycemia, but resulted in subjective discomfort and a lower state of arousal (as indicated by lower heart rate and EDA). These may underly the trend for more missed responses on the 2-back task after breakfast skipping. Noise appeared to generate arousal and increased attention (reflected in higher EDA and P300) in accordance with higher experienced load and stress. This is consistent with less missed 2-back responses in noise conditions. The results indicate that individuals spent extra effort to maintain task performance in the presence of noise. We propose to use a model that, besides additional effort, takes the effect of stressors on performance into account.

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