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70 results for “eye-tracking”
QAVA-DPC: Eye-Tracking Based Quality Assessment and Visual Attention Dataset for Dynamic Point Cloud in 6 DoF
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Assessing the impact of central and peripheral obstructions on visual behavior: insights from gaze-contingent eye-tracking studies
<p>This dataset is a collection of image stimuli, as well as gaze tracks collected using visual field masks, such as central and peripheral scotoma, in order to assess the way people with visual field loss process visual stimuli in digital environments.</p> <h3><strong>This dataset is structured as follows :</strong></h3> <ul> <li>Stimuli: 125 fullHD images (1920x1080) used during the experiment trials; 4 fullHD images used during the training phase.</li> <li>Trials_metadata: <ul> <li>Psychopy_outputs: various callbacks and logs files from the Psychopy experiment</li> <li>trials_metadata: .csv files containing metadata such as stimuli order and timestamps.</li> </ul> </li> <li>Raw_eyetracking_outputs: subfolders containing the raw .edf files output by the Eyelink 1000+ eye-tracker. .edf files are divided into groups of 25 successive stimuli displayed.</li> <li>Raw_gaze_points: .csv files, containing the raw gaze points locations for each subject, stimulus and mask. Blinks, invalid coordinates and out-of-bounds gaze points are already removed from these files.</li> <li>Fixations: .csv files (one per image per participant) containing eye fixations locations extracted from the raw gaze points using a I-VT algorithm with a saccade velocity threshold of 45 deg/s.</li> </ul> <h2><br><strong>Experiment</strong></h2> <h3>Images</h3> <p>This database consists of 100 images collected from personal collections and various public image datasets, such as the CityScapes and the KITTI-360 datasets, covering a variety of themes, including landscapes, people, actions, and nature.<br>Images had a 1920 x 1080 pixel resolution (FullHD) and were shown on a screen with the same resolution. </p> <h3>Eye-tracking data collection</h3> <p>The stimuli were presented to a group of 37 observers, with normal or corrected-to-normal vision. We used a table-mounted EyeLink 1000 Plus eye-tracker, working at a fixed rate of 1000Hz, with a chin rest to ensure data accuracy. Participants were informed that they would observe images both with and without simulated visual field impairments, and the two types of masks used were described. They were also told that the only task is to view the images freely. </p> <p>To familiarize participants with the different types of masks, four training images (distinct from the trial dataset) were provided in the training phase, with each image presented in the three conditions -- peripheral mask, foveal mask, and control (no mask) -- with varying mask sizes. <br>In the trial phase, stimuli were displayed in a random order, with a randomly generated playlist ensuring no three consecutive stimuli were of the same image. A uniform gray screen was displayed between each stimulus. </p> <p>Viewing distance was set to be 90cm.<br>Eye-tracker calibration was carried out using a 9-point calibration protocol, i.e., 9 points were sequentially and randomly shown on the screen, where the observer should fixate their gaze. <br>Additionally, calibration was performed after every 25 displayed images.</p> <p>Each image was presented to the observers for a 5-second period.</p> <p>Each image in the database was presented to the observers under different conditions :<br> - The image without any obstruction, referred to as the control condition (C). <br> - Peripheral mask (P) simulating a tunnel vision, with two circular mask size variations (one individual mask for each eye): 1.5° and 4.5° radius of field of view, referred to as P1 and P2, respectively. <br> - Foveal mask (F) simulating a central scotoma, also with two size variations: 1.5° and 4.5° radius of obstruction, referred to as F1 and F2, in that order.</p> <p> </p>
Las técnicas de eye-tracking aplicadas al estudio experimental de la eficacia publicitaria de campañas de PRL en la Juventud
<p>Video resumen de un artículo presentado en el VI Congreso Latinoamericano de Marketing Social en Brasil</p>
eye-tracking data from a survey on zooming in a pan-scalar map
<p><strong>Recording and processing a survey using an eye tracker </strong></p> <p>The eye-tracker used is a Pupil Core from Pupil Labs. The basic eye tracker configuration, i.e. a fixation time of 80 ms to 200 ms, is kept for this experiment.</p> <p> </p> <p>The aim of the experiment is to understand what a person looks at to find their way around a multi-scale map and to understand the different strategies used. To do this, the user will be free to use the map as he wishes, i.e. he can use pan and zoom at will. Four types of tasks will be asked in order to have a maximum of types of use of multi-scale map.The first task is to simulate that a user is using an application like map or Google map and is looking for a specific address. The map application will then zoom in very strongly on the address. The user has little spatial context and it often takes some time to find his way around. To simulate the application, a point is placed on Paris or its surroundings and the display is very zoomed (Paris was chosen because most people have a more or less detailed mental map of Paris). The user is then asked to interact with the map (zooming and panning) until he feels he is sufficiently located, as he would if he had to search for a place on his mobile phone. When he is located, he just needs to move on to the next stage without asking for validation. This stage is carried out in four locations. The four points are located near Montmartre, at the entrance to the catacombs of Paris, in Vincennes and finally at Porte d'Asnières</p> <p><br> The second task is to find a place from an aerial image. The aerial image of a specific area is displayed and the map is zoomed out to the city where the location is located. The user must then try to find the location in the image. Unlike the first task, the user must request validation before proceeding to the next stage.<br> This task is repeated in two different cities. The two images are the tête d'or park in Lyon and a building block next to a railway in Dijon.</p> <p><br> The third task also consists of finding a precise location using textual indications. The user still has to ask for validation to go to the next stage .</p> <p>This task is repeated in two different cities.The first was "to find the town hall which is just south of the town centre and next to the library" and the second was "to find the stadium east of the town centre and north of the river Vilaine with a north/south orientation.</p> <p><br> The last task builds on tasks 2 and 3. The map is again zoomed out, an aerial image appears and textual indications are given. This task is repeated on two different cities.</p> <p>The first image is of a building in beauvais with the indication: "the building is in the north west of sqare next to the SNCF station". The second one is a picture of a stadium in lyon with the indication: "the stadium is west of the confluence of lyon".</p> <p><strong>data format :</strong><br> <strong>Coord_fixation_on_map_x_y</strong>: geolocated fixation point with x the survey type 1 or 2 and y the candidate number (id_fixation,x,y,zoom,etape)</p> <p><strong>Pan</strong>: pan on the map during the survey</p> <p><strong>Pan_fixation_on_map</strong> : fixation during a pan</p> <p><strong>zoom</strong>: zoom on the map during the survey</p> <p><strong>zoom_fixation_on_map</strong>: fixation during a zoom</p> <p><strong>stat</strong>: number of zoom, pan and fixation per step</p> <p><strong>result_map_x </strong>= map status every 100 ms during the survey x</p> <p><strong>00x </strong>: export file of the eye-tracker pupil Lab</p> <p> </p>
Assessing Code Readability in Python Programming Courses Using Eye-Tracking - Python Code Snippets
<p>Python code snippets for assessing code readability in Python programming courses using eye-tracking.</p>
Immersive Virtual REality for Treatment of Unilateral Spatial NEglect Via Eye-tracking Biofeedback
ClinicalTrials.gov study NCT06264713. IPD Sharing: NO. Countries: 1. Publications: 10.
Eye-tracking Technology for Severe Communication Disability
ClinicalTrials.gov study NCT05808478. IPD Sharing: Not stated. Countries: 1. Publications: 3.
The Effects of Losartan on Attention Control: An Eye-tracking Study
ClinicalTrials.gov study NCT06329050. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Oral Vasopressin Modulates Neural Responses to Looming Visual Stimuli: An Eye-tracking Study
ClinicalTrials.gov study NCT06329063. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Losartan Modulates Neural Responses to Looming Visual Stimuli: An Eye-tracking Study
ClinicalTrials.gov study NCT06329076. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Development of Eye-tracking Based Markers for Autism in Young Children
ClinicalTrials.gov study NCT03286621. IPD Sharing: NO. Countries: 1. Publications: 1.
Annotated Eye-Tracking Data for Attention and Inattention in ASD
<p>This data included a total of 20 children with mild to moderate ASD (ASD n = 20, mean age = 8.57, SD = 1.40), 16 boys and 4 girls within the age of 7–11 years. The participants were recruited from an Autism School in Doha and Qatar Autism Society. All the participants had a formal diagnosis of mild to moderate ASD and met the requirements for the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM IV). All participants reported normal vision. </p> <p>Eye-tracking data were recorded using a screen-based Tobii X<sub>2</sub>-60 eye-tracking device with a sampling rate of 60 Hz. The Eye-tracking device was attached to the base of the 24-inch computer screen set aside for each participant. The visual attention task was simulated with a desktop virtual reality application that presents a continuous performance test (VR-CPT). This test simulates a conventional learning environment with a teacher in front of a classroom, other students seated, ceiling lights, windows, and a door. The VR-CPT presents distractors similar to that of a real classroom simultaneously with random alphabets displayed on the board. The random letters are used as the target stimuli in this experiment where the participant needs to press the clicker when the letter X appears and ignores other letters. </p>
Data from: A novel system for bi-ocular eye-tracking in vertebrates with laterally placed eyes
1. Animals use vision to gather information about their environment and then use that information to make behavioural decisions that affect fitness. They will often move their heads or eyes to inspect areas of interest with their centres of acute vision, such as foveae, to gather high resolution information about potential mates, predation risks, or other aspects of the environment. Few studies to date have been able to accurately determine where laterally eyed animals direct their visual attention and how they use their eyes to gather information. 2. We present a non-invasive eye-tracking system that can simultaneously track the gaze of two eyes. This is particularly useful for studying animals with laterally placed eyes (most vertebrates) where the two eyes are viewing different images. This system can also accommodate comparative studies using animals of varying size, including small animals that are not frequently used in eye-tracking studies due to constraints of existing eye-tracking systems. We conducted an eye-tracking experiment with European starlings (Sturnus vulgaris) to test the eye-tracking system, calibration methods and highlight relevant aspects of experimental design. 3. We were able to accurately track the gaze of European starlings with <5 degrees of error. We also found that starlings are more likely to fixate on biologically relevant visual stimuli (e.g. predators and active prey) than simple stimuli (e.g. a dot) in video playbacks. 4. The method presented here can be used to address ecological and evolutionary questions about where animals direct their attention and how they visually inspect mates, food and predators, as well as address management questions about how animals inspect man-made objects. This method can also be used to answer fundamental questions about vision, such as how laterally eyed vertebrates coordinate the use of their eyes laterally and binocularly.
Attentional bias for physical activity: eye-tracking data
<p><strong>Dataset related to the paper entitled "Physically active individuals look for more: An eye tracking study of attentional bias". </strong></p> <p>This dataset includes:</p> <p>1) A workbook</p> <p>2) Raw data of the behavioral outcome (i.e., reaction times) of the visual dot probe task</p> <p>"dpt_sample1_27_05_2019.csv" for the sample 1.</p> <p>"dpt_sample2_27_05_2019.csv" for the sample 2.</p> <p>3) Raw data of the eye-tracking outcomes (i.e., Gaze Data)</p> <p>4) Self-reported data</p> <p>"data_all_SR.Rdata" for the sample 1</p> <p>"data_SR1_inhib.RData" for the sample 2</p> <p>4) R script for the data management of the raw RT</p> <p>"Data_management_DPT_RT.R". This script leads to the file "dpt_behavioral_both_sample.RData", which merges the behavioral data of both sample with the self-reported data.</p> <p>5) Raw data of the eye-tracking outcomes</p> <p>"Data_management_DPT_Gaze_13_06_2019". This script leads to the file "dpt_both_sample_EyeTrack.RData", which merge the gaze data of both sample with the self-reported data.</p> <p>6) R script for the models tested on the behavioral and eye-tracking outcomes</p> <p>"Models_zenodo"</p> <p>7) the visual dot probe task (e-prime script)</p> <p>"DPT_Eyetracker.7z". This file contains the e-prime script as well as the images used in the visual dot probe task</p>
Eye-tracking Working Memory Training in Children and Youth With Severe Cerebral Palsy
ClinicalTrials.gov study NCT06918379. IPD Sharing: NO. Countries: 1. Publications: 0.
RCT for Gambling and Naltrexone, Using Use Eye-tracking Analysis to Predict Treatment Response
ClinicalTrials.gov study NCT04738773. IPD Sharing: UNDECIDED. Countries: 0. Publications: 30.
Visual Perception Exploration Using Eye-tracking Technology in High-fidelity Medical Simulation
ClinicalTrials.gov study NCT03049098. IPD Sharing: NO. Countries: 0. Publications: 5.
Data from: A novel system for bi-ocular eye-tracking in vertebrates with laterally placed eyes
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Eye-tracking Statistics of Effectiveness Evaluation of Rectangular Cartogram
<p>Eye-tracking data collected in the evaluation for conveying quantitative data. Full description will be provided after the paper is accepted.</p>
Inspiration From Eye-tracking Data: Investigating the Impact of Combining Specific Environmental Features and Power Mobility Training
ClinicalTrials.gov study NCT06928077. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.