We overview recent research in Child-Computer Interaction and describe our framework ChildCI intended for: i) generating a better understanding of the cognitive and neuromotor development of children while interacting with mobile devices, and ii) enabling new applications in e-learning and e-health, 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 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. Different machine learning approaches are evaluated, proposing a new set of 34 global features to automatically detect age groups, achieving accuracy results over 90% and interesting findings in terms of the type of features more useful for this task.
翻译:我们审视了儿童-计算机互动的最新研究,并描述了我们的儿童信息中心(ChildCI)框架,目的是:(一) 更好地了解儿童在与移动设备互动时的认知和神经运动发育,以及(二) 促成电子学习和电子保健等方面的新应用,我们的框架包括一个新的移动应用程序、具体的数据获取协议和首次发布儿童信息中心数据集(ChildCIb v1),计划每年扩展该数据集,以便能够进行纵向研究。在我们的框架中,儿童与平板设备互动,使用笔状和手指,执行不同程度的神经运动和认知技能的不同任务。儿童信息中心由400多名18个月至8岁的儿童组成,因此考虑到Piaget理论的前三个发展阶段。此外,作为儿童信息中心框架潜力的示范,我们还包括儿童信息中心所促成的许多应用程序之一的实验结果:根据设备互动情况对儿童年龄进行检测。对不同的机器学习方法进行了评估,提出了一套由34个新的全球特征组成的新组合,用于自动检测年龄组,实现90%以上准确性结果,以及这一任务类型中令人感兴趣的研究结果。