CRII: CHS: Adaptive Virtual Environments for a Prolonged Exposure Therapy of Attention Deficits on Autism Spectrum

这项研究的目标是开发和评估一种自适应虚拟现实（VR）系统，该系统将为自闭症谱系中注意力缺陷的儿童提供创新疗法。近年来，美国自闭症谱系障碍（ASD）的患病率显著增长，虽然已经有一些成功的努力通过利用基于VR的疗法来解决这个问题，但其中大多数只是使用VR作为模拟现有方法的替代方法。VR技术的一个重要特征--能够产生“不可能的体验”（即，在真实的世界中无法创建的体验，例如椅子在用户的注视下消失）-在这些系统中似乎缺失，因为当大多数传统ASD疗法被开发时，该特征不可用。设想的系统将采用专门设计的“不可能的体验”来提供个性化治疗，以解决ASD儿童的注意力缺陷。该研究将提高ASD儿童的学习能力，并为未来用于ASD治疗的VR系统提供新的设计指南。PI将研究研究问题并逐步开发系统。系统的总体逻辑是：1）将用户暴露于虚拟环境以完成任务（例如，听虚拟老师讲话）; 2）用眼睛跟踪数据和生理信号检测用户的注意力，然后去除所有检测到的干扰（例如，红色马克杯）; 3）逐渐地将所有干扰恢复到虚拟环境中，一次将用户暴露于一个或多个干扰对象，并加强正确的注意力。为了实施这一策略，PI将首先通过短期用户研究探索VR中的注意力捕获以及VR中的强化策略。然后，整个系统的有效性将通过为期六个月的多基线设计的参与者研究进行评估。所有的研究将与K-12的学生进行中到高水平的ASD。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

The goal of this research is to develop and evaluate an adaptive virtual reality (VR) system that will enable an innovative therapy for children with attention deficit on the autism spectrum. The prevalence of autism spectrum disorder (ASD) in the United State has grown significantly in recent years, and while there have been some successful efforts to address this issue by exploiting VR-based therapies, most of them merely use VR as an alternative way to simulate existing approaches. An important feature of VR technology - the ability to generate "impossible experiences" (i.e., experiences that cannot be created in the real world, such as a chair disappearing upon the user's gaze) - seems to be missing in these systems, because this feature was not available when most traditional ASD therapies were developed. The envisaged system will employ specifically designed "impossible experiences" to deliver an individualized therapy that addresses the attention deficits of children with ASD. The research will improve the learning ability for children with ASD and provide novel design guidelines for future VR systems used in ASD therapy. The PI will study research questions and develop the system incrementally. The overall logic of the system is: 1) Expose the user to a virtual environment to finish a task (e.g., listen to a virtual teacher talking); 2) Detect the user's attention with eye-tracking data and physiological signals, then remove all the detected distractions (e.g., a red mug) from the virtual environment; 3) Gradually restore all distractions into the virtual environment, expose the user to one more distraction object at a time and reinforce the correct attention. To implement this strategy, the PI will first explore attention capture in VR and strategies for reinforcement in VR through short user studies. Then, the effectiveness of the entire system will be evaluated through a six-month long, multiple-baseline design across participants study. All the studies will be conducted with K-12 students with medium to high levels of ASD.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.