Emotional Expression Processing and Depressive Symptomatology: Eye-Tracking Reveals Differential Importance of Lower and Middle Facial Areas of Interest

The current study explored the eye-tracking patterns of individuals with nonclinical levels of depressive symptomatology when processing emotional expressions. Fifty-three college undergraduates were asked to label 80 facial expressions of five emotions (anger, fear, happiness, neutral, and sadness) while an eye-tracker measured visit duration. We argue visit duration provides more detailed information for evaluating which features of the face are used more often for processing emotional faces. Our findings indicated individuals with nonclinical levels of depressive symptomatology process emotional expressions very similarly to individuals with little to no depressive symptoms, with one noteworthy exception. In general, individuals in our study visited the “T” region, lower and middle AOIs (Area of Interest), more often than upper and noncore areas, but the distinction between the lower and middle AOIs appears for happiness only when individuals are higher in depressive symptoms.

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The Use of Eye Tracking to Discern the Threshold at Which Metopic Orbitofrontal Deformity Attracts Attention

The Cleft Palate-Craniofacial Journal ◽

10.1177/1055665620926014 ◽

2020 ◽

Vol 57 (12) ◽

pp. 1392-1401

Author(s):

Mark P. Pressler ◽

Emily L. Geisler ◽

Rami R. Hallac ◽

James R. Seaward ◽

Alex A. Kane

Keyword(s):

Surgical Treatment ◽

Graduate Students ◽

Eye Tracking ◽

Dwell Time ◽

Surgical Intervention ◽

Three Dimensional ◽

Average Dwell Time ◽

Eye Tracker ◽

Gaze Patterns ◽

Areas Of Interest

Introduction and Objectives: Surgical treatment for trigonocephaly aims to eliminate a stigmatizing deformity, yet the severity that captures unwanted attention is unknown. Surgeons intervene at different points of severity, eliciting controversy. This study used eye tracking to investigate when deformity is perceived. Material and Methods: Three-dimensional photogrammetric images of a normal child and a child with trigonocephaly were mathematically deformed, in 10% increments, to create a spectrum of 11 images. These images were shown to participants using an eye tracker. Participants’ gaze patterns were analyzed, and participants were asked if each image looked “normal” or “abnormal.” Results: Sixty-six graduate students were recruited. Average dwell time toward pathologic areas of interest (AOIs) increased proportionally, from 0.77 ± 0.33 seconds at 0% deformity to 1.08 ± 0.75 seconds at 100% deformity ( P < .0001). A majority of participants did not agree an image looked “abnormal” until 90% deformity from any angle. Conclusion: Eye tracking can be used as a proxy for attention threshold toward orbitofrontal deformity. The amount of attention toward orbitofrontal AOIs increased proportionally with severity. Participants did not generally agree there was “abnormality” until deformity was severe. This study supports the assertion that surgical intervention may be best reserved for more severe deformity.

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The spatial distribution of eye movements predicts the (false) recognition of emotional facial expressions

PLoS ONE ◽

10.1371/journal.pone.0245777 ◽

2021 ◽

Vol 16 (1) ◽

pp. e0245777

Author(s):

Fanny Poncet ◽

Robert Soussignan ◽

Margaux Jaffiol ◽

Baptiste Gaudelus ◽

Arnaud Leleu ◽

...

Keyword(s):

Spatial Distribution ◽

Eye Movements ◽

Eye Tracking ◽

Facial Expressions ◽

False Recognition ◽

Recognition Task ◽

Visual Exploration ◽

Emotional Expressions ◽

Facial Emotions ◽

The Face

Recognizing facial expressions of emotions is a fundamental ability for adaptation to the social environment. To date, it remains unclear whether the spatial distribution of eye movements predicts accurate recognition or, on the contrary, confusion in the recognition of facial emotions. In the present study, we asked participants to recognize facial emotions while monitoring their gaze behavior using eye-tracking technology. In Experiment 1a, 40 participants (20 women) performed a classic facial emotion recognition task with a 5-choice procedure (anger, disgust, fear, happiness, sadness). In Experiment 1b, a second group of 40 participants (20 women) was exposed to the same materials and procedure except that they were instructed to say whether (i.e., Yes/No response) the face expressed a specific emotion (e.g., anger), with the five emotion categories tested in distinct blocks. In Experiment 2, two groups of 32 participants performed the same task as in Experiment 1a while exposed to partial facial expressions composed of actions units (AUs) present or absent in some parts of the face (top, middle, or bottom). The coding of the AUs produced by the models showed complex facial configurations for most emotional expressions, with several AUs in common. Eye-tracking data indicated that relevant facial actions were actively gazed at by the decoders during both accurate recognition and errors. False recognition was mainly associated with the additional visual exploration of less relevant facial actions in regions containing ambiguous AUs or AUs relevant to other emotional expressions. Finally, the recognition of facial emotions from partial expressions showed that no single facial actions were necessary to effectively communicate an emotional state. In contrast, the recognition of facial emotions relied on the integration of a complex set of facial cues.

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Use of Eye-Tracking Technology by Medical Students Taking the Objective Structured Clinical Examination: Descriptive Study

Journal of Medical Internet Research ◽

10.2196/17719 ◽

2020 ◽

Vol 22 (8) ◽

pp. e17719

Author(s):

M D Grima-Murcia ◽

Francisco Sanchez-Ferrer ◽

Jose Manuel Ramos-Rincón ◽

Eduardo Fernández

Keyword(s):

Medical Students ◽

Eye Tracking ◽

Clinical Examination ◽

Objective Evaluation ◽

Objective Structured Clinical Examination ◽

Eye Tracker ◽

Clinical Competencies ◽

Self Evaluation ◽

Areas Of Interest ◽

Tracking Technology

Background The objective structured clinical examination (OSCE) is a test used throughout Spain to evaluate the clinical competencies, decision making, problem solving, and other skills of sixth-year medical students. Objective The main goal of this study is to explore the possible applications and utility of portable eye-tracking systems in the setting of the OSCE, particularly questions associated with attention and engagement. Methods We used a portable Tobii Glasses 2 eye tracker, which allows real-time monitoring of where the students were looking and records the voice and ambient sounds. We then performed a qualitative and a quantitative analysis of the fields of vision and gaze points attracting attention as well as the visual itinerary. Results Eye-tracking technology was used in the OSCE with no major issues. This portable system was of the greatest value in the patient simulators and mannequin stations, where interaction with the simulated patient or areas of interest in the mannequin can be quantified. This technology proved useful to better identify the areas of interest in the medical images provided. Conclusions Portable eye trackers offer the opportunity to improve the objective evaluation of candidates and the self-evaluation of the stations used as well as medical simulations by examiners. We suggest that this technology has enough resolution to identify where a student is looking at and could be useful for developing new approaches for evaluating specific aspects of clinical competencies.

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Computer-generated facial areas of interest in eye tracking research: A simulation study

10.31234/osf.io/nam3x ◽

2021 ◽

Author(s):

Antonia Vehlen ◽

William Standard ◽

Gregor Domes

Keyword(s):

Eye Tracking ◽

Voronoi Tessellation ◽

Data Accuracy ◽

Type I ◽

Type Ii ◽

Eye Tracker ◽

Type I Errors ◽

Areas Of Interest ◽

Type Ii Errors ◽

The Impact

Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer’s test conditions, validation is essential with regard to data quality and other factors potentially threatening data validity. In this study, we evaluated the impact of data accuracy and areas of interest (AOIs) size on the classification of simulated gaze data. We defined AOIs of different sizes using the Limited-Radius Voronoi-Tessellation (LRVT) method, and simulated gaze data for facial target points with varying data accuracy. As hypothesized, we found that data accuracy and AOI size had strong effects on gaze classification. In addition, these effects were not independent and differed for falsely classified gaze inside AOIs (Type I errors) and falsely classified gaze outside the predefined AOIs (Type II errors). The results indicate that smaller AOIs generally minimize false classifications as long as data accuracy is good enough. For studies with lower data accuracy, Type II errors can still be compensated to some extent by using larger AOIs, but at the cost of an increased probability of Type I errors. Proper estimation of data accuracy is therefore essential for making informed decisions regarding the size of AOIs.

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Eye-tracking based quantification of the safety of human-machine interfaces of complementary protective system functions

International Journal of Occupational and Environmental Safety ◽

10.24840/2184-0954_005.002_0001 ◽

2021 ◽

Vol 5 (2) ◽

pp. 1-13

Author(s):

Julian Zehetner ◽

Ivo Häring ◽

Ulrich Weber ◽

Werner Riedel

Keyword(s):

Eye Tracking ◽

Preliminary Test ◽

Human Interaction ◽

Protective Measures ◽

Area Of Interest ◽

Human Machine Interfaces ◽

Test Parameters ◽

Protective System ◽

Visit Duration ◽

Tracking Technology

Complementary protective measures are of increasing importance with rising degree of automation. As free robots become part of our daily life in industry, on shop floors and beyond, the overall safety of persons has to be ensured. However, assessing the reliability of complementary safety functions remains a challenge, particularly when humans are in the loop. The paper shows how to use the eye-tracking methodology to gain data for assessing the reliability of the human interaction with machine interfaces for complementary protective measures. The paper first identifies factors relevant for eye-tracking, then selects related eye tracking test parameters and finally provides a systematic procedure to assess both, in particular regarding visibility and susceptibility. The methodology is applied and the parameter selection is validated. It is found that in particular the identified and measured parameters fixation count for area of interest (AOI) and the associated average visit duration can be used to assess the factor perceptibility. The parameter deviation of fixation can thereby be used to assess usability. Based on this, a full-scale eye-tracking assessment is proposed for the reliability of the interaction of humans with the machine interfaces of supplementary protective measures. In summary, the preliminary test run execution shows that eye-tracking technology is a promising method for measuring and quantifying the human reliability when interacting with safety-related human-machine interfaces.

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Use of Eye-Tracking Technology by Medical Students Taking the Objective Structured Clinical Examination: Descriptive Study (Preprint)

10.2196/preprints.17719 ◽

2020 ◽

Author(s):

M D Grima-Murcia ◽

Francisco Sanchez-Ferrer ◽

Jose Manuel Ramos-Rincón ◽

Eduardo Fernández

Keyword(s):

Medical Students ◽

Eye Tracking ◽

Clinical Examination ◽

Objective Evaluation ◽

Objective Structured Clinical Examination ◽

Eye Tracker ◽

Clinical Competencies ◽

Self Evaluation ◽

Areas Of Interest ◽

Tracking Technology

BACKGROUND The objective structured clinical examination (OSCE) is a test used throughout Spain to evaluate the clinical competencies, decision making, problem solving, and other skills of sixth-year medical students. OBJECTIVE The main goal of this study is to explore the possible applications and utility of portable eye-tracking systems in the setting of the OSCE, particularly questions associated with attention and engagement. METHODS We used a portable Tobii Glasses 2 eye tracker, which allows real-time monitoring of where the students were looking and records the voice and ambient sounds. We then performed a qualitative and a quantitative analysis of the fields of vision and gaze points attracting attention as well as the visual itinerary. RESULTS Eye-tracking technology was used in the OSCE with no major issues. This portable system was of the greatest value in the patient simulators and mannequin stations, where interaction with the simulated patient or areas of interest in the mannequin can be quantified. This technology proved useful to better identify the areas of interest in the medical images provided. CONCLUSIONS Portable eye trackers offer the opportunity to improve the objective evaluation of candidates and the self-evaluation of the stations used as well as medical simulations by examiners. We suggest that this technology has enough resolution to identify where a student is looking at and could be useful for developing new approaches for evaluating specific aspects of clinical competencies.

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EVALUATION OF COLOR SETTINGS IN AERIAL IMAGES WITH THE USE OF EYE-TRACKING USER STUDY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b3-763-2016 ◽

2016 ◽

Vol XLI-B3 ◽

pp. 763-767

Author(s):

J. Mirijovsky ◽

S. Popelka

Keyword(s):

Eye Tracking ◽

User Study ◽

Aerial Images ◽

Eye Tracker ◽

Lighting Conditions ◽

Graphic Editor ◽

Real Value ◽

Crop Area ◽

Different Color ◽

Areas Of Interest

The main aim of presented paper is to find the most realistic and preferred color settings for four different types of surfaces on the aerial images. This will be achieved through user study with the use of eye-movement recording. Aerial images taken by the unmanned aerial system were used as stimuli. From each image, squared crop area containing one of the studied types of surfaces (asphalt, concrete, water, soil, and grass) was selected. For each type of surface, the real value of reflectance was found with the use of precise spectroradiometer ASD HandHeld 2 which measures the reflectance. The device was used at the same time as aerial images were captured, so lighting conditions and state of vegetation were equal. The spectral resolution of the ASD device is better than 3.0 nm. For defining the RGB values of selected type of surface, the spectral reflectance values recorded by the device were merged into wider groups. Finally, we get three groups corresponding to RGB color system. Captured images were edited with the graphic editor Photoshop CS6. Contrast, clarity, and brightness were edited for all surface types on images. Finally, we get a set of 12 images of the same area with different color settings. These images were put into the grid and used as stimuli for the eye-tracking experiment. Eye-tracking is one of the methods of usability studies and it is considered as relatively objective. Eye-tracker SMI RED 250 with the sampling frequency 250 Hz was used in the study. As respondents, a group of 24 students of Geoinformatics and Geography was used. Their task was to select which image in the grid has the best color settings. The next task was to select which color settings they prefer. Respondents’ answers were evaluated and the most realistic and most preferable color settings were found. The advantage of the eye-tracking evaluation was that also the process of the selection of the answers was analyzed. Areas of Interest were marked around each image in the grid and the sequences of gaze movements were analyzed. Sequence chart was used for visualization and eye-tracking metrics were statistically tested. The presented paper shows the differences in the perception and preferences of aerial images with different color settings.

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The Application of Flexible Areas of Interest to Pilot Mobile Eye Tracking

Sensors ◽

10.3390/s20040986 ◽

2020 ◽

Vol 20 (4) ◽

pp. 986

Author(s):

Zbigniew Gomolka ◽

Damian Kordos ◽

Ewa Zeslawska

Keyword(s):

Eye Tracking ◽

Video Stream ◽

Flight Training ◽

Area Of Interest ◽

Human Machine Interfaces ◽

Dynamic Tracking ◽

Definition Of ◽

The Individual ◽

Areas Of Interest ◽

Mobile Eye Tracking

Recent progress in the development of mobile Eye Tracking (ET) systems shows that there is a demand for modern flexible solutions that would allow for dynamic tracking of objects in the video stream. The paper describes a newly developed tool for work with ET glasses, and its advantages are outlined with the example of a pilot study. A flight task is performed on the FNTP II MCC simulator, and the pilots are equipped with the Mobile Tobii Glasses. The proposed Smart Trainer tool performs dynamic object tracking in a registered video stream, allowing for an interactive definition of Area of Interest (AOI) with blurred contours for the individual cockpit instruments and for the construction of corresponding histograms of pilot attention. The studies are carried out on a group of experienced pilots with a professional pilot CPL(A) license with instrumental flight (Instrument Rating (IR)) certification and a group of pilots without instrumental training. The experimental section shows the differences in the perception of the flight process between two distinct groups of pilots with varying levels in flight training for the ATPL(A) line pilot license. The proposed Smart Trainer tool might be exploited in order to assess and improve the process of training operators of advanced systems with human machine interfaces.

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Eye tracking metrics and leader’s behavioral performance during a post-partum hemorrhage high-fidelity simulated scenario

Advances in Simulation ◽

10.1186/s41077-021-00156-2 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Emanuele Capogna ◽

Giorgio Capogna ◽

Denise Raccis ◽

Francesco Salvi ◽

Matteo Velardo ◽

...

Keyword(s):

Eye Tracking ◽

Team Performance ◽

Postpartum Hemorrhage ◽

Post Partum ◽

Eye Contact ◽

Assessment Process ◽

High Fidelity ◽

Eye Tracker ◽

Sources Of Information ◽

Areas Of Interest

Abstract Background The use of eye tracking in the simulated setting can help improve our understanding of what sources of information clinicians are using as they deliver routine patient care. The aim of this simulation study was to observe the differences, if any, between the eye tracking patterns of leaders who performed best in a simulated postpartum hemorrhage (PPH) high-fidelity scenario, in comparison with those who performed worst. Methods Forty anesthesia trainees from the University of Catania Medical School were divided into eight teams, to enact four times the same scenario of a patient with postpartum hemorrhage following vaginal delivery. Trainees who were assigned the leader’s role wore the eye tracking glasses during the scenario, and their behavioral skills were evaluated by two observers, who reviewed the video recordings of the scenarios using a standardized checklist. The leader’s eye tracking metrics, extracted from 27 selected areas of interest (AOI), were recorded by a Tobii Pro Glasses 50 Hz wearable wireless eye tracker. Team performance was evaluated using a PPH checklist. After completion of the study, the leaders were divided into two groups, based on the scores they had received (High-Performance Leader group, HPL, and Low-Performance Leader group, LPL). Results In the HPL group, the duration and number of fixations were greater, and the distribution of gaze was uniformly distributed among the various members of the team as compared with the LPL group (with the exception of the participant who performed the role of the obstetrician). The HPL group also looked both at the patient’s face and established eye contact with their team members more often and for longer (P < .05). The team performance (PPH checklist) score was greater in the HPL group (P < .001). The LPL group had more and/or longer fixations of technical areas of interest (P < .05). Conclusions Our findings suggest that the leaders who perform the best distribute their gaze across all members of their team and establish direct eye contact. They also look longer at the patient’s face and dwell less on areas that are more relevant to technical skills. In addition, the teams led by these best performing leaders fulfilled their clinical task better. The information provided by the eye behaviors of “better-performing physicians” may lay the foundation for the future development of both the assessment process and the educational tools used in simulation. Trial Registration Clinical.Trial.Gov ID n. NCT04395963.

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

Behavior Research Methods ◽

10.3758/s13428-021-01544-2 ◽

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.

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