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      Remote Eye-Tracking for Cognitive Telerehabilitation and Interactive School Tasks in Times of COVID-19

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          Abstract

          In the attempt to mitigate the effects of COVID-19 lockdown, most countries have recently authorized and promoted the adoption of e-learning and remote teaching technologies, often with the support of teleconferencing platforms. Unfortunately, not all students can benefit from the adoption of such a surrogate of their usual school. We were asked to devise a way to allow a community of children affected by the Rett genetic syndrome, and thus unable to communicate verbally, in writing or by gestures, to actively participate in remote rehabilitation and special education sessions by exploiting eye-gaze tracking. As not all subjects can access commercial eye-tracking devices, we investigated new ways to facilitate the access to eye gaze-based interaction for this specific case. The adopted communication platform is a videoconferencing software, so all we had at our disposal was a live video stream of the child. As a solution to the problem, we developed a software (named SWYG) that only runs at the “operator” side of the communication, at the side of the videoconferencing software, and does not require to install other software in the child’s computer. The preliminary results obtained are very promising and the software is ready to be deployed on a larger base. While this paper is being written, several children are finally able to communicate with their caregivers from home, without relying on expensive and cumbersome devices.

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          Most cited references22

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          Rett syndrome: revised diagnostic criteria and nomenclature.

          Rett syndrome (RTT) is a severe neurodevelopmental disease that affects approximately 1 in 10,000 live female births and is often caused by mutations in Methyl-CpG-binding protein 2 (MECP2). Despite distinct clinical features, the accumulation of clinical and molecular information in recent years has generated considerable confusion regarding the diagnosis of RTT. The purpose of this work was to revise and clarify 2002 consensus criteria for the diagnosis of RTT in anticipation of treatment trials. RettSearch members, representing the majority of the international clinical RTT specialists, participated in an iterative process to come to a consensus on a revised and simplified clinical diagnostic criteria for RTT. The clinical criteria required for the diagnosis of classic and atypical RTT were clarified and simplified. Guidelines for the diagnosis and molecular evaluation of specific variant forms of RTT were developed. These revised criteria provide clarity regarding the key features required for the diagnosis of RTT and reinforce the concept that RTT is a clinical diagnosis based on distinct clinical criteria, independent of molecular findings. We recommend that these criteria and guidelines be utilized in any proposed clinical research.
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            Technoference: Parent Distraction With Technology and Associations With Child Behavior Problems.

            Heavy parent digital technology use has been associated with suboptimal parent-child interactions, but no studies examine associations with child behavior. This study investigates whether parental problematic technology use is associated with technology-based interruptions in parent-child interactions, termed "technoference," and whether technoference is associated with child behavior problems. Parent reports from 170 U.S. families (child Mage  = 3.04 years) and actor-partner interdependence modeling showed that maternal and paternal problematic digital technology use predicted greater technoference in mother-child and father-child interactions; then, maternal technoference predicted both mothers' and fathers' reports of child externalizing and internalizing behaviors. Results suggest that technological interruptions are associated with child problem behaviors, but directionality and transactional processes should be examined in future longitudinal studies.
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              MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation

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                Author and article information

                Journal
                INFOGG
                Information
                Information
                MDPI AG
                2078-2489
                June 2020
                June 01 2020
                : 11
                : 6
                : 296
                Article
                10.3390/info11060296
                c279d46b-d4b1-4530-bba9-4bdb2fd1bdca
                © 2020

                https://creativecommons.org/licenses/by/4.0/

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