Child-Computer Interaction with Mobile Devices: Recent Works, New Dataset, and Age Detection
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Abstract (arXiv)
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 pen stylus and the finger, performing different tasks that require different levels of neuromotor and cognitive skills. ChildCIdb is the first database in the literature that comprises more than 400 children from 18 months to 8 years old, considering therefore the first three development stages of the Piaget's theory. In addition, and as a demonstration of the potential of the ChildCI framework, we include experimental results for one of the many applications enabled by ChildCIdb: children age detection based on device interaction.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 4 of its 47 references that are in the map. First posted on arXiv 2 Feb 2021.
Builds on
4 of 47 references.
References · 4
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- 2020DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representationscited by 26
- 2020Heart Rate Estimation from Face Videos for Student Assessment: Experiments on edBBcited by 12
- 2019Characterization of the Handwriting Skills as a Biomarker for Parkinson Diseasecited by 5
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
3 papers.
- 2021GaitPrivacyON: Privacy-Preserving Mobile Gait Biometrics using Unsupervised Learningcited by 8
- 2022ChildCI Framework: Analysis of Motor and Cognitive Development in Children-Computer Interaction for Age Detectioncited by 2
- 2026Longitudinal Digital Phenotyping for Early Cognitive-Motor Screeningcited by 0
- 2026Longitudinal Digital Phenotyping for Early Cognitive-Motor Screening26 Mar 2026
- 2022ChildCI Framework: Analysis of Motor and Cognitive Development in Children-Computer Interaction for Age Detection8 Apr 2022
- 2021GaitPrivacyON: Privacy-Preserving Mobile Gait Biometrics using Unsupervised Learning8 Oct 2021