Longitudinal Analysis and Quantitative Assessment of Child Development through Mobile Interaction
<|reference_start|>Longitudinal Analysis and Quantitative Assessment of Child Development through Mobile Interaction: This article provides a comprehensive overview of recent research in the area of Child-Computer Interaction (CCI). The main contributions of the present article are two-fold. First, we present a novel longitudinal CCI database named ChildCIdbLong, which comprises over 600 children aged 18 months to 8 years old, acquired continuously over 4 academic years (2019-2023). As a result, ChildCIdbLong comprises over 12K test acquisitions over a tablet device. Different tests are considered in ChildCIdbLong, requiring different touch and stylus gestures, enabling the evaluation of praxical and cognitive skills such as attentional, visuo-spatial, and executive, among others. In addition to the ChildCIdbLong database, we propose a novel quantitative metric called Test Quality (Q), designed to measure the motor and cognitive development of children through their interaction with a tablet device. In order to provide a better comprehension of the proposed Q metric, popular percentile-based growth representations are introduced for each test, providing a two-dimensional space to compare children's development with respect to the typical age skills of the population. The results achieved in the present article highlight the potential of the novel ChildCIdbLong database in conjunction with the proposed Q metric to measure the motor and cognitive development of children as they grow up. The proposed framework could be very useful as an automatic tool to support child experts (e.g., paediatricians, educators, or neurologists) for early detection of potential physical/cognitive impairments during children's development.<|reference_end|>
@article{ruiz-garcia2024longitudinal,
    title={Longitudinal Analysis and Quantitative Assessment of Child Development
  through Mobile Interaction},
    author={Juan Carlos Ruiz-Garcia, Ruben Tolosana, Ruben Vera-Rodriguez, Aythami
  Morales, Julian Fierrez, Javier Ortega-Garcia, Jaime Herreros-Rodriguez},
    journal={IEEE Access, 2024},
    year={2024},
    doi={10.1109/ACCESS.2024.3446455},
    archivePrefix={arXiv},
    eprint={2404.06919},
    primaryClass={cs.HC}
}