Practice Track: A Learning Tracker using Digital Biomarkers for Autistic Preschoolers

Gurmit S. Sandhu, A. Kilburg, A. Martin, Charuta Pande, Hans Friedrich Witschel, Emanuele Laurenzi, E. Billing
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引用次数: 1

Abstract

Preschool children, when diagnosed with Autism Spectrum Disorder (ASD), often ex- perience a long and painful journey on their way to self-advocacy. Access to standard of care is poor, with long waiting times and the feeling of stigmatization in many social set- tings. Early interventions in ASD have been found to deliver promising results, but have a high cost for all stakeholders. Some recent studies have suggested that digital biomarkers (e.g., eye gaze), tracked using affordable wearable devices such as smartphones or tablets, could play a role in identifying children with special needs. In this paper, we discuss the possibility of supporting neurodiverse children with technologies based on digital biomark- ers which can help to a) monitor the performance of children diagnosed with ASD and b) predict those who would benefit most from early interventions. We describe an ongoing feasibility study that uses the “DREAM dataset”, stemming from a clinical study with 61 pre-school children diagnosed with ASD, to identify digital biomarkers informative for the child’s progression on tasks such as imitation of gestures. We describe our vision of a tool that will use these prediction models and that ASD pre-schoolers could use to train certain social skills at home. Our discussion includes the settings in which this usage could be embedded.
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练习跟踪:使用数字生物标记的自闭症学龄前儿童学习跟踪器
学龄前儿童在被诊断为自闭症谱系障碍(ASD)时,往往会经历一段漫长而痛苦的自我辩护之旅。获得标准护理的机会很少,等待时间长,在许多社会环境中有被污名化的感觉。对自闭症谱系障碍的早期干预已被发现能产生有希望的结果,但对所有利益相关者来说成本都很高。最近的一些研究表明,使用智能手机或平板电脑等价格合理的可穿戴设备跟踪的数字生物标志物(例如,眼睛注视)可以在识别有特殊需求的儿童方面发挥作用。在本文中,我们讨论了基于数字生物标记的技术支持神经多样性儿童的可能性,这些技术可以帮助a)监测被诊断为ASD的儿童的表现,b)预测那些将从早期干预中获益最多的儿童。我们描述了一项正在进行的可行性研究,该研究使用“DREAM数据集”,源于61名被诊断为ASD的学龄前儿童的临床研究,以确定儿童在模仿手势等任务上的进展信息的数字生物标志物。我们描述了我们对一种工具的愿景,这种工具将使用这些预测模型,并且ASD学龄前儿童可以使用它在家里训练某些社交技能。我们的讨论包括可以嵌入这种用法的设置。
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