基于行为跟踪的自适应和个性化视觉支持在自闭症儿童互惠和协调技能评估中的应用

T. Tang, Pinata Winoto
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引用次数: 1

摘要

最近的研究已经证明了活动和行为模式分析机制的适用性,可以帮助治疗师、护理人员和患有发育障碍的个体,包括自闭症谱系障碍(ASD);这种行为建模系统的计算成本和复杂性可能会阻碍它们的部署。因此,在本文中,我们提出了一个易于部署的自动系统来训练联合注意(JA)技能,评估互惠的频率和程度,并相应地提供视觉提示。我们提出的方法与大多数早期的尝试不同,因为我们没有利用复杂的特征空间构建方法;相反,简单的设计,游戏内的自动数据收集为自适应视觉支持提供了无障碍的好处,特别是对于低功能的ASD患者和那些有严重语言障碍的人。
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Providing Adaptive and Personalized Visual Support based on Behavioral Tracking of Children with Autism for Assessing Reciprocity and Coordination Skills in a Joint Attention Training Application
Recent works have demonstrated the applicability of the activity and behavioral pattern analysis mechanisms to assist therapists, care-givers and individuals with development disorders including those with autism spectrum disorder (ASD); the computational cost and sophistication of such behavioral modeling systems might prevent them from deploying. As such, in this paper, we proposed an easily deployable automatic system to train joint attention (JA) skills, assess the frequency and degree of reciprocity and provide visual cues accordingly. Our proposed approach is different from most of earlier attempts in that we do not capitalize the sophisticated feature-space construction methodology; instead, the simple design, in-game automatic data collection for adaptive visual supports offers hassle-free benefits especially for low-functioning ASD individuals and those with severe verbal impairments.
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IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22 - 25, 2022 Employing Social Media to Improve Mental Health: Pitfalls, Lessons Learned, and the Next Frontier IUI '21: 26th International Conference on Intelligent User Interfaces, College Station, TX, USA, April 13-17, 2021 Towards Making Videos Accessible for Low Vision Screen Magnifier Users. SaIL: Saliency-Driven Injection of ARIA Landmarks.
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