This article presents a comprehensive analysis of the different tests proposed in the recent ChildCI framework, proving its potential for generating a better understanding of children's neuromotor and cognitive development along time, as well as their possible application in other research areas such as e-Health and e-Learning. In particular, we propose a set of over 100 global features related to motor and cognitive aspects of the children interaction with mobile devices, some of them collected and adapted from the literature. Furthermore, we analyse the robustness and discriminative power of the proposed feature set including experimental results for the task of children age group detection based on their motor and cognitive behaviours. Two different scenarios are considered in this study: i) single-test scenario, and ii) multiple-test scenario. Results over 93% accuracy are achieved using the publicly available ChildCIdb_v1 database (over 400 children from 18 months to 8 years old), proving the high correlation of children's age with the way they interact with mobile devices.

翻译：本文对近期ChildCI框架中提出的各类测试进行了全面分析，证明了其在深入理解儿童神经运动与认知发展随时间变化规律方面的潜力，以及其在电子健康与电子学习等其他研究领域的应用可能性。具体而言，我们提出了一套包含100余项与儿童移动设备交互过程中运动与认知特征相关的全局特征集，其中部分特征系从文献中收集并改编而成。此外，我们通过基于儿童运动与认知行为进行年龄组检测任务的实验结果，分析了所提特征集的鲁棒性和判别能力。本研究考虑两种场景：i)单一测试场景，ii)多测试场景。基于公开可用的ChildCIdb_v1数据库（涵盖400余名18个月至8岁儿童），实验取得了超过93%的准确率，充分证明儿童年龄与其移动设备交互方式的高度相关性。