ChildCI framework: Analysis of motor and cognitive development in children-computer interaction for age detection

IF 2.1 3区心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Cognitive Systems Research Pub Date : 2024-03-21 DOI:10.1016/j.cogsys.2024.101230

Juan Carlos Ruiz-Garcia , Ruben Tolosana , Ruben Vera-Rodriguez , Julian Fierrez , Jaime Herreros-Rodriguez

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引用次数: 0

Abstract

This article presents a comprehensive analysis of the different tests proposed in the recent ChildCI framework,¹ 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.

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ChildCI 框架：分析儿童与计算机互动中的运动和认知发展以检测年龄

本文全面分析了最近提出的儿童智能（ChildCI）框架1 中的各种测试，证明该框架具有更好地了解儿童神经运动和认知随时间发展的潜力，以及在电子健康和电子学习等其他研究领域的应用可能性。此外，我们还分析了所提特征集的鲁棒性和辨别力，包括根据运动和认知行为检测儿童年龄组任务的实验结果。本研究考虑了两种不同的情况：(i) 单次测试情况；(ii) 多次测试情况。使用公开的 ChildCIdb_v1 数据库（超过 400 名 18 个月至 8 岁的儿童），结果准确率超过 93%，证明了儿童年龄与他们与移动设备交互的方式高度相关。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cognitive Systems Research 工程技术-计算机：人工智能

CiteScore

9.40

自引率

5.10%

发文量

审稿时长

>12 weeks

期刊介绍： Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.