scholarly journals PyTrack: An end-to-end analysis toolkit for eye tracking

2020 ◽  
Vol 52 (6) ◽  
pp. 2588-2603
Author(s):  
Upamanyu Ghose ◽  
Arvind A. Srinivasan ◽  
W. Paul Boyce ◽  
Hong Xu ◽  
Eng Siong Chng
Keyword(s):  
Statistical Analysis ◽  
Eye Movements ◽  
Eye Tracking ◽  
Automated Analysis ◽  
Movement Behavior ◽  
High Temporal Resolution ◽  
Technological Advancement ◽  
Tracking Data ◽  
End To End ◽  
Parameters Of Interest

AbstractEye tracking is a widely used tool for behavioral research in the field of psychology. With technological advancement, we now have specialized eye-tracking devices that offer high sampling rates, up to 2000 Hz, and allow for measuring eye movements with high accuracy. They also offer high spatial resolution, which enables the recording of very small movements, like drifts and microsaccades. Features and parameters of interest that characterize eye movements need to be algorithmically extracted from raw data as most eye trackers identify only basic parameters, such as blinks, fixations, and saccades. Eye-tracking experiments may investigate eye movement behavior in different groups of participants and in varying stimuli conditions. Hence, the analysis stage of such experiments typically involves two phases, (i) extraction of parameters of interest and (ii) statistical analysis between different participants or stimuli conditions using these parameters. Furthermore, the datasets collected in these experiments are usually very large in size, owing to the high temporal resolution of the eye trackers, and hence would benefit from an automated analysis toolkit. In this work, we present PyTrack, an end-to-end open-source solution for the analysis and visualization of eye-tracking data. It can be used to extract parameters of interest, generate and visualize a variety of gaze plots from raw eye-tracking data, and conduct statistical analysis between stimuli conditions and subject groups.

scholarly journals Spontaneous eye-movements during eyes-open rest reduce resting-state-network modularity by increasing visual-sensorimotor connectivity

2021 ◽  
pp. 1-39
Author(s):  
Cemal Koba ◽  
Giuseppe Notaro ◽  
Sandra Tamm ◽  
Gustav Nilsonne ◽  
Uri Hasson
Keyword(s):  
Eye Movements ◽  
Eye Tracking ◽  
Resting State ◽  
Movement Control ◽  
Clustering Coefficient ◽  
Tracking Data ◽  
Planar Imaging ◽  
Experimental Conditions ◽  
Sensory Motor ◽  
Eyes Open

During wakeful rest, individuals make small eye movements during fixation. We examined how these endogenously-driven oculomotor patterns impact topography and topology of functional brain networks. We used a dataset consisting of eyes-open resting-state (RS) fMRI data with simultaneous eye-tracking (Nilsonne et al., 2016). The eye-tracking data indicated minor movements during rest, which correlated modestly with RS BOLD data. However, eye-tracking data correlated well with echo-planar imaging time series sampled from the area of the Eye-Orbit (EO-EPI), which is a signal previously used to identify eye movements during exogenous saccades and movie viewing. Further analyses showed that EO-EPI data were correlated with activity in an extensive motor and sensory-motor network, including components of the dorsal attention network and the frontal eye fields. Partialling out variance related to EO-EPI from RS data reduced connectivity, primarily between sensory-motor and visual areas. It also produced networks with higher modularity, lower mean connectivity strength, and lower mean clustering coefficient. Our results highlight new aspects of endogenous eye movement control during wakeful rest. They show that oculomotor-related contributions form an important component of RS network topology, and that those should be considered in interpreting differences in network structure between populations, or as a function of different experimental conditions.

scholarly journals Spontaneous eye-movements during eyes-open rest reduce resting-state-network modularity by increasing visual-sensorimotor connectivity

2020 ◽  
Author(s):  
Cemal Koba ◽  
Giuseppe Notaro ◽  
Sandra Tamm ◽  
Gustav Nilsonne ◽  
Uri Hasson
Keyword(s):  
Eye Movements ◽  
Eye Tracking ◽  
Resting State ◽  
Movement Control ◽  
Clustering Coefficient ◽  
Tracking Data ◽  
Planar Imaging ◽  
Experimental Conditions ◽  
Sensory Motor ◽  
Eyes Open

ABSTRACTDuring wakeful rest, individuals make small eye movements when asked to fixate. We examined how these endogenously-driven oculomotor patterns impact topography and topology of functional brain networks. We used a dataset consisting of eyes-open resting-state (RS) fMRI data with simultaneous eye-tracking (Nilsonne et al., 2016). The eye-tracking data indicated minor movements during rest, on the order of 1.0 degree on average when analyzed over 2sec epochs, which correlated modestly with RS BOLD data. However, the eye-tracking data correlated well with echo-planar imaging (EPI) time series sampled from the area of the Eye-Orbit (EO-EPI), which is a signal previously used to identify eye movements during exogenous saccades and movie viewing. We found that EO-EPI data correlated with activity in an extensive motor and sensory-motor network, but also some components of the dorsal attention network including the frontal and supplementary eye fields. Partialling out variance related to EO-EPI from RS data reduced connectivity, primarily between sensory-motor and visual areas. For three different network sparsity levels, the resulting RS connectivity networks showed higher modularity, lower mean connectivity strength, and lower mean clustering coefficient. Our results highlight new aspects of endogenous eye movement control during wakeful rest. They show that oculomotor-related contributions form an important component of RS network topology, and that those should be considered in interpreting differences in network structure between populations, or as a function of different experimental conditions.

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.

scholarly journals Translators’ Use of Digital Resources During Translation

2017 ◽  
pp. 71 ◽  
Author(s):  
Kristian Tangsgaard Hvelplund
Keyword(s):  
Eye Movements ◽  
Eye Tracking ◽  
Cognitive Load ◽  
Tracking Data ◽  
Translation Process ◽  
Digital Resources ◽  
Use Of Resources ◽  
Digital Resource

This paper presents the findings from a study on translators’ use of digital resources during the translation process. Eye tracking data and screen recording data from 18 professional translators are analysed in order to 1) examine how much time translators spend on digital resource consultation compared with translation drafting and translation revision, 2) examine how eye movements differ between translation drafting, revision and digital resource consultation and 3) investigate what types of digital resources are used by translators. The findings demonstrate that digital resource consultation constitutes a considerable amount of the translation process. The findings also show longer fixations and larger pupils during resource consultation, indicating heavier cognitive load, and finally the study identifies considerable variation in the use of resources between translators.

scholarly journals Collaborative Use of a Shared System Interface: The Role of User Gaze—Gaze Convergence Index Based on Synchronous Dual-Eyetracking

2020 ◽  
Vol 10 (13) ◽  
pp. 4508 ◽  
Author(s):  
Armel Quentin Tchanou ◽  
Pierre-Majorique Léger ◽  
Jared Boasen ◽  
Sylvain Senecal ◽  
Jad Adam Taher ◽  
...  
Keyword(s):  
Eye Movements ◽  
Eye Tracking ◽  
Task Performance ◽  
Tracking Data ◽  
Nomological Network ◽  
Practical Applications ◽  
The Gaze ◽  
Research Perspectives ◽  
System Interfaces

Gaze convergence of multiuser eye movements during simultaneous collaborative use of a shared system interface has been proposed as an important albeit sparsely explored construct in human-computer interaction literature. Here, we propose a novel index for measuring the gaze convergence of user dyads and address its validity through two consecutive eye-tracking studies. Eye-tracking data of user dyads were synchronously recorded while they simultaneously performed tasks on shared system interfaces. Results indicate the validity of the proposed gaze convergence index for measuring the gaze convergence of dyads. Moreover, as expected, our gaze convergence index was positively associated with dyad task performance and negatively associated with dyad cognitive load. These results suggest the utility of (theoretical or practical) applications such as synchronized gaze convergence displays in diverse settings. Further research perspectives, particularly into the construct’s nomological network, are warranted.

scholarly journals Random Spray Retinex Extensions Considering Region of Interest and Eye Movements

2019 ◽  
Vol 63 (6) ◽  
pp. 60403-1-60403-6
Author(s):  
Midori Tanaka ◽  
Matteo Paolo Lanaro ◽  
Takahiko Horiuchi ◽  
Alessandro Rizzi
Keyword(s):  
Information Processing ◽  
Eye Movements ◽  
Visual Field ◽  
Eye Tracking ◽  
Mathematical Description ◽  
Visual Information ◽  
Tracking System ◽  
Region Of Interest ◽  
Tracking Data ◽  
Proposed Model

Abstract The Random spray Retinex (RSR) algorithm was developed by taking into consideration the mathematical description of Milano-Retinex. The RSR substituted random paths with random sprays. Mimicking some characteristics of the human visual system (HVS), this article proposes two variants of RSR adding a mechanism of region of interest (ROI). In the first proposed model, a cone distribution based on anatomical data is considered as ROI. In the second model, the visual resolution depending on the visual field based on the knowledge of visual information processing is considered as ROI. We have measured actual eye movements using an eye-tracking system. By using the eye-tracking data, we have simulated the HVS using test images. Results show an interesting qualitative computation of the appearance of the processed area around real gaze points.

Investigation of cue-based vertical and horizontal eye movements with electroencephalographic and eye-tracking data

2009 ◽  
Vol 120 (11) ◽  
pp. 1988-1993 ◽  
Author(s):  
Vera Kaiser ◽  
Clemens Brunner ◽  
Robert Leeb ◽  
Christa Neuper ◽  
Gert Pfurtscheller
Keyword(s):  
Eye Movements ◽  
Eye Tracking ◽  
Tracking Data

scholarly journals Random Spray Retinex Extensions Considering Region of Interest and EyeMovements

2020 ◽  
Vol 2020 (15) ◽  
pp. 60403-1-60403-6
Author(s):  
Midori Tanaka ◽  
Matteo Paolo Lanaro ◽  
Takahiko Horiuchi ◽  
Alessandro Rizzi
Keyword(s):  
Information Processing ◽  
Eye Movements ◽  
Visual Field ◽  
Eye Tracking ◽  
Mathematical Description ◽  
Visual Information ◽  
Tracking System ◽  
Region Of Interest ◽  
Tracking Data ◽  
Proposed Model

The Random spray Retinex (RSR) algorithm was developed by taking into consideration the mathematical description of Milano-Retinex. The RSR substituted random paths with random sprays. Mimicking some characteristics of the human visual system (HVS), this article proposes two variants of RSR adding a mechanism of region of interest (ROI). In the first proposed model, a cone distribution based on anatomical data is considered as ROI. In the second model, the visual resolution depending on the visual field based on the knowledge of visual information processing is considered as ROI. We have measured actual eye movements using an eye-tracking system. By using the eye-tracking data, we have simulated the HVS using test images. Results show an interesting qualitative computation of the appearance of the processed area around real gaze points.

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