Child-Computer Interaction with Mobile Devices: Recent Works, New Dataset, and Age Detection
Ruben Tolosana, Juan Carlos Ruiz-Garcia, Ruben Vera-Rodriguez, Jaime, Herreros-Rodriguez, Sergio Romero-Tapiador, Aythami Morales, Julian Fierrez

TL;DR
This paper reviews recent child-computer interaction research with mobile devices, introduces the ChildCI framework and dataset for longitudinal studies, and demonstrates age detection from interaction data to support e-learning and health applications.
Contribution
It presents a new large-scale, publicly available dataset of children's interactions with tablets, and a framework for studying cognitive and neuromotor development over time.
Findings
ChildCIdb contains data from over 400 children aged 18 months to 8 years.
Demonstrated age detection accuracy using interaction data.
Framework supports longitudinal and multi-modal studies in child development.
Abstract
This article provides an overview of recent research in Child-Computer Interaction with mobile devices and describe our framework ChildCI intended for: i) overcoming the lack of large-scale publicly available databases in the area, ii) generating a better understanding of the cognitive and neuromotor development of children along time, contrary to most previous studies in the literature focused on a single-session acquisition, and iii) enabling new applications in e-Learning and e-Health through the acquisition of additional information such as the school grades and children's disorders, among others. Our framework includes a new mobile application, specific data acquisition protocols, and a first release of the ChildCI dataset (ChildCIdb v1), which is planned to be extended yearly to enable longitudinal studies. In our framework children interact with a tablet device, using both a…
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