Longitudinal Analysis and Quantitative Assessment of Child Development through Mobile Interaction

Fuente: arXiv
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Main Authors: Ruiz-Garcia, Juan Carlos, Tolosana, Ruben, Vera-Rodriguez, Ruben, Morales, Aythami, Fierrez, Julian, Ortega-Garcia, Javier, Herreros-Rodriguez, Jaime
Format: Preprint
Published: 2024
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author Ruiz-Garcia, Juan Carlos
Tolosana, Ruben
Vera-Rodriguez, Ruben
Morales, Aythami
Fierrez, Julian
Ortega-Garcia, Javier
Herreros-Rodriguez, Jaime
author_facet Ruiz-Garcia, Juan Carlos
Tolosana, Ruben
Vera-Rodriguez, Ruben
Morales, Aythami
Fierrez, Julian
Ortega-Garcia, Javier
Herreros-Rodriguez, Jaime
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2404_06919
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Longitudinal Analysis and Quantitative Assessment of Child Development through Mobile Interaction
Ruiz-Garcia, Juan Carlos
Tolosana, Ruben
Vera-Rodriguez, Ruben
Morales, Aythami
Fierrez, Julian
Ortega-Garcia, Javier
Herreros-Rodriguez, Jaime
Human-Computer 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.
title Longitudinal Analysis and Quantitative Assessment of Child Development through Mobile Interaction
topic Human-Computer Interaction
url https://arxiv.org/abs/2404.06919