Systematic mapping of the literature on mobile apps for people with Autistic Spectrum Disorder

Maico Krause, Macilon Araújo Costa Neto
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引用次数: 3

Abstract

The advancement of mobile technologies combined with assistive technologies can provide autonomy to people with different types of disabilities, including those with Autistic Spectrum Disorder (ASD). Technologies, such as those found in mobile devices, are very attractive to people with ASD and can be used as a valuable educational tool for these individuals. The aim of this study was to learn about how mobile apps aimed at people with ASD are developed and evaluated, carried out through a systematic mapping of applications aimed at people with ASD, in order to better understand their foundations, motivations, evaluation mode, resources and user profile. The results indicated that the main procedures used to support the applications for people with ASD are the questionnaires to identify the ASD, such as the CHAT and AQ-10, and the ABA intervention, and that these applications, mostly, seek to identify the ASD in a practical way and at a low cost. Most of the apps were evaluated by usability testing and through indirect observation through the app's logs. The most used hardware and software resources are the mobile device camera and convolutional neural networks (CNN), respectively, with most applications aimed at children and the most common software engineering methodologies were requirements analysis and prototyping.
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针对自闭症谱系障碍患者的移动应用程序的文献系统映射
移动技术的进步与辅助技术相结合,可以为不同类型的残疾人,包括自闭症谱系障碍(ASD)患者提供自主性。技术,比如在移动设备中发现的技术,对自闭症患者非常有吸引力,可以作为这些人有价值的教育工具。本研究的目的是了解针对ASD患者的移动应用程序是如何开发和评估的,通过对针对ASD患者的应用程序进行系统的映射,以便更好地了解它们的基础、动机、评估模式、资源和用户概况。结果表明,支持ASD患者申请的主要程序是识别ASD的问卷,如CHAT和AQ-10,以及ABA干预,这些应用大多寻求以实用和低成本的方式识别ASD。大多数应用都是通过可用性测试和间接观察应用日志来评估的。使用最多的硬件和软件资源分别是移动设备摄像头和卷积神经网络(CNN),大多数应用程序针对儿童,最常见的软件工程方法是需求分析和原型设计。
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