Product Body Shapes, Not Features, Provide Fast and Frugal Cues for Environmental Friendliness

2016 ◽  
Author(s):  
Ping Du ◽  
Erin F. MacDonald
Keyword(s):  
Eye Tracking ◽  
Visual Cues ◽  
Body Shape ◽  
Visual Design ◽  
Tracking Data ◽  
Mental Load ◽  
Environmental Friendliness ◽  
Visual Areas ◽  
Body Shapes ◽  
Areas Of Interest

Mental associations between a product’s visual design and its unobservable characteristics aid consumer judgments. It is hypothesized these associations, or cues, allow people to decrease the mental load required to make a decision. This paper investigates the rapid-building of mental associations between visual cues and unobservable attributes. It questions if it is more effective to cue holistically, through body-shape, or by individual features. Subjects participated in an association-building task and were then surveyed for retention of positive and negative cues for environmental friendliness ratings. Results demonstrate retention of body shapes cues but not feature cues. Additionally, eye-tracking data demonstrate that people redistribute their attention to a product after the association-building task, increasing the percentage of attention in the cued visual areas-of-interest. This supports the hypothesis that cues work to distribute mental load more efficiently; subjects’ evaluations became more targeted when judging environmental friendliness.

A Test of the Rapid Formation of Design Cues for Product Body Shapes and Features

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Ping Du ◽  
Erin F. MacDonald
Keyword(s):  
Visual Cues ◽  
Body Shape ◽  
Environmentally Friendly ◽  
The Body ◽  
General Idea ◽  
Visual Design ◽  
Mental Load ◽  
Environmental Friendliness ◽  
Body Shapes ◽  
Tracking Device

Consumers often use a product's visual design as a mental shortcut to judge its unobservable attributes. Mental associations between visual design and unobservable attributes aid consumers in their judgments, and hypothetically reduce consumers' mental load. This paper describes a study that shows the possibility of quickly creating an association in subjects' minds between a holistic visual cue of a product—its body shape—and the general idea of “environmentally friendly” versus “not environmentally friendly,” a typically unobservable attribute. In this study, products' actual environmental friendliness was not measured. Subjects completed an association-building task, in which they developed mental associations between a product's visual cues and its “environmental friendliness” rating, an arbitrarily predetermined rating the authors supplied. The body shape was successfully used as a cue to subliminally communicate to subjects the product's “environmental friendliness.” As a comparison, an individual feature of the product was also used to cue; however, that was unsuccessful. An eye-tracking device was used to identify where subjects were focusing their eyes and for how long. In both the association-building task and a testing task that followed, subjects spent a greater percentage of time looking at the product's cued areas (the body and the selected feature). But during the testing task, subjects spent an even higher percentage of their time looking at the cued areas than they did during the association-building task. This indicates that mental associations, or cues, work to distribute mental load more efficiently.

Identification of Temporally Varying Areas of Interest in Long-Duration Eye-Tracking Data Sets

2019 ◽  
Vol 25 (1) ◽  
pp. 87-97 ◽  
Author(s):  
Prithiviraj K. Muthumanickam ◽  
Katerina Vrotsou ◽  
Aida Nordman ◽  
Jimmy Johansson ◽  
Matthew Cooper
Keyword(s):  
Eye Tracking ◽  
Data Sets ◽  
Tracking Data ◽  
Long Duration ◽  
Areas Of Interest

Rapid Preparation of Eye Tracking Data For Debriefing In Medical Training: A Feasibility Study

2019 ◽  
Vol 63 (1) ◽  
pp. 733-737
Author(s):  
E. Wolf ◽  
R. Heinrich ◽  
A. Michalek ◽  
D. Schraudt ◽  
A. Hohm ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Feasibility Study ◽  
Medical Training ◽  
Future Research ◽  
Distribution Data ◽  
Tracking Data ◽  
Rapid Preparation ◽  
Patient Simulator ◽  
Technical Performance ◽  
Areas Of Interest

Simulation-based medical training is an increasingly used method to improve the technical and non-technical performance of clinical staff. An essential part of training is the debriefing of the participants, often using audio, video, or even eye tracking recordings. We conducted a practice-oriented feasibility study to test an eye tracking data preparation procedure, which automatically provided information about the gaze distribution on areas of interest such as the vital sign monitor or the patient simulator. We acquired eye tracking data during three simulation scenarios and provided gaze distribution data for debriefing within 30 minutes. Additionally, we qualitatively evaluated the usefulness of the generated eye tracking data for debriefings. Participating students and debriefers were mostly positive about the data provided; however, future research should improve the technical side of the procedure and investigate best practices regarding how to present and use the data in debriefings.

scholarly journals An Exploratory Application of Eye-Tracking Methods in a Discrete Choice Experiment

2018 ◽  
Vol 38 (6) ◽  
pp. 658-672 ◽  
Author(s):  
Caroline Vass ◽  
Dan Rigby ◽  
Kelly Tate ◽  
Andrew Stewart ◽  
Katherine Payne
Keyword(s):  
Decision Making ◽  
Eye Tracking ◽  
Risk Communication ◽  
Discrete Choice ◽  
Dwell Time ◽  
Ordinary Least Squares ◽  
Discrete Choice Experiments ◽  
Tracking Data ◽  
Significant Difference ◽  
Areas Of Interest

Background. Discrete choice experiments (DCEs) are increasingly used to elicit preferences for benefit-risk tradeoffs. The primary aim of this study was to explore how eye-tracking methods can be used to understand DCE respondents’ decision-making strategies. A secondary aim was to explore if the presentation and communication of risk affected respondents’ choices. Method. Two versions of a DCE were designed to understand the preferences of female members of the public for breast screening that varied in how risk attributes were presented. Risk was communicated as either 1) percentages or 2) icon arrays and percentages. Eye-tracking equipment recorded eye movements 1000 times a second. A debriefing survey collected sociodemographics and self-reported attribute nonattendance (ANA) data. A heteroskedastic conditional logit model analyzed DCE data. Eye-tracking data on pupil size, direction of motion, and total visual attention (dwell time) to predefined areas of interest were analyzed using ordinary least squares regressions. Results. Forty women completed the DCE with eye-tracking. There was no statistically significant difference in attention (fixations) to attributes between the risk communication formats. Respondents completing either version of the DCE with the alternatives presented in columns made more horizontal (left-right) saccades than vertical (up-down). Eye-tracking data confirmed self-reported ANA to the risk attributes with a 40% reduction in mean dwell time to the “probability of detecting a cancer” ( P = 0.001) and a 25% reduction to the “risk of unnecessary follow-up” ( P = 0.008). Conclusion. This study is one of the first to show how eye-tracking can be used to understand responses to a health care DCE and highlighted the potential impact of risk communication on respondents’ decision-making strategies. The results suggested self-reported ANA to cost attributes may not be reliable.

scholarly journals Eye-tracking glasses in face-to-face interactions: Manual versus automated assessment of areas-of-interest

2021 ◽  
Author(s):  
Chiara Jongerius ◽  
T. Callemein ◽  
T. Goedemé ◽  
K. Van Beeck ◽  
J. A. Romijn ◽  
...  
Keyword(s):  
Computer Vision ◽  
Eye Tracking ◽  
Interrater Reliability ◽  
Tracking Data ◽  
Dynamic Interactions ◽  
Area Of Interest ◽  
Gaze Behaviour ◽  
Vision Algorithm ◽  
Areas Of Interest ◽  
Mobile Eye Tracking

AbstractThe assessment of gaze behaviour is essential for understanding the psychology of communication. Mobile eye-tracking glasses are useful to measure gaze behaviour during dynamic interactions. Eye-tracking data can be analysed by using manually annotated areas-of-interest. Computer vision algorithms may alternatively be used to reduce the amount of manual effort, but also the subjectivity and complexity of these analyses. Using additional re-identification (Re-ID) algorithms, different participants in the interaction can be distinguished. The aim of this study was to compare the results of manual annotation of mobile eye-tracking data with the results of a computer vision algorithm. We selected the first minute of seven randomly selected eye-tracking videos of consultations between physicians and patients in a Dutch Internal Medicine out-patient clinic. Three human annotators and a computer vision algorithm annotated mobile eye-tracking data, after which interrater reliability was assessed between the areas-of-interest annotated by the annotators and the computer vision algorithm. Additionally, we explored interrater reliability when using lengthy videos and different area-of-interest shapes. In total, we analysed more than 65 min of eye-tracking videos manually and with the algorithm. Overall, the absolute normalized difference between the manual and the algorithm annotations of face-gaze was less than 2%. Our results show high interrater agreements between human annotators and the algorithm with Cohen’s kappa ranging from 0.85 to 0.98. We conclude that computer vision algorithms produce comparable results to those of human annotators. Analyses by the algorithm are not subject to annotator fatigue or subjectivity and can therefore advance eye-tracking analyses.

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 TO THE QUESTION OF PECULIARITIES OF EYE MOVEMENT ANALYSIS IN THE PROCESS OF FACE PERCEPTION

2021 ◽  
pp. 196-219
Author(s):  
Galina Ya. Menshikova ◽  
Anna O. Pichugina
Keyword(s):  
Eye Movements ◽  
Eye Tracking ◽  
Eye Movement ◽  
Face Perception ◽  
Dwell Time ◽  
Holistic Processing ◽  
Facial Features ◽  
Tracking Data ◽  
Individual Strategies ◽  
Areas Of Interest

Background. The article is devoted to the study of the mechanisms of face perception when using the technology of eye-tracking. In the scientific literature, two processes are distinguished - analytical (perception of individual facial features) and holistic (perception of a general configuration of facial features). It is assumed that each of the mechanisms can be specifically manifested in patterns of eye movements during face perception. However, there is disagreement among the authors concerning the eye movements patterns which reflect the dominance of the holistic or analytic processing. We hypothesized that the contradictions in the interpretation of eye movement indicators in the studies of face perception may be associated with the features of the eye-tracker data processing, namely, with the specifics of identifying areas of interest (eyes, nose, bridge of the nose, lips), as well as with individual strategies of eye movements. Objective. Revealing the features of eye movements analysis in the process of facial perception. Method. A method for studying analytical and holistic processing in the task of assessing the attractiveness of upright and inverted faces using eye-tracking technology has been developed and tested. The eye-tracking data were analyzed for the entire sample using three types of processing, differing in the marking of the areas of interest (AOIs), and separately for two groups differing in eye movement strategies. The distinction of strategies was considered based on differences in the mean values of the fixation duration and the amplitude of saccades. Results. It was shown that: the presence of statistically significant differences of the dwell time in the AOIs between the condition of upright and inverted faces depended on the method of identifying these AOIs. It was shown that the distribution of the dwell time by zones is closely related to individual strategies of eye movements. Analysis of the data separately by groups showed significant differences in the distribution of the dwell time in the AOIs. Conclusion. When processing eye-tracking data obtained in the studies of face perception, it is necessary to consider individual strategies of eye movements, as well as the features associated with identifying AOIs. The absence of a single standard for identifying these areas can be the reason for inconsistency of the data about the holistic or analytical processing dominance. According to our data, the most effective for the analysis of holistic processing is a more detailed type of marking the AOIs, in which not only the main features (eyes, nose, mouth) are distinguished, but also the area of the nose bridge and nose.

Eye-Tracking Data Predict Importance of Product Features and Saliency of Size Change

2014 ◽  
Vol 136 (8) ◽  
Author(s):  
Ping Du ◽  
Erin F. MacDonald
Keyword(s):  
Eye Tracking ◽  
Visual Design ◽  
Fixation Time ◽  
Tracking Data ◽  
Size Change ◽  
Visual Appearance ◽  
Customer Preference ◽  
Product Features ◽  
Customer Evaluations ◽  
Feature Importance

Features, or visible product attributes, are indispensable product components that influence customer evaluations of functionality, usability, symbolic impressions, and other qualities. Two basic components of features are visual appearance and size. This work tests whether or not eye-tracking data can (1) predict the relative importances between features, with respect to their visual design, in overall customer preference and (2) identify how much a feature must change in size in order to be noticeable by the viewer. The results demonstrate that feature importance is significantly correlated with a variety of gaze data. Results also show that there are significant differences in fixation time and count for noticeable versus unnoticeable size changes. Statistical models of gaze data can predict feature importance and saliency of size change.

scholarly journals Open-source Software for Determining the Dynamic Areas of Interest for Eye Tracking Data Analysis

2021 ◽  
Vol 192 ◽  
pp. 2568-2575
Author(s):  
Leszek Bonikowski ◽  
Dawid Gruszczyński ◽  
Jacek Matulewski
Keyword(s):  
Data Analysis ◽  
Eye Tracking ◽  
Open Source ◽  
Open Source Software ◽  
Tracking Data ◽  
Areas Of Interest
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