Adaptive Response Technology for Autism Spectrum Disorders Intervention

自闭症谱系障碍干预的自适应响应技术

• 批准号: 8049922
• 负责人: NILANJAN SARKAR
• 金额: $ 34.99万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-12-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8049922
• 关键词: Adaptive Behaviors; Address; Adolescent; Adult; Affect; Affective; Applications Grants; Area; Attention; Behavior Therapy; Behavioral; Behavioral Model; Biofeedback; Centers for Disease Control and Prevention (U.S.); Characteristics; Child; Child Development; Cognitive; Computers; Controlled Clinical Trials; Data; Development; Disease; Disease remission; Educational Intervention; Environment; Expert Systems; Eye; Failure; Goals; Heterogeneity; Impairment; Individual; Intervention; Language; Learning; Longevity; Longitudinal Studies; Methodology; Modality; Modeling; Modification; Nature; Outcome; Participant; Performance; Physiological; Physiology; Prevalence; Psychological reinforcement; Public Health; Relative (related person); Research; Resources; School-Age Population; Science; Social Behavior; Social Functioning; System; Task Performances; Technology; Time; United States; Variant; Work; autism spectrum disorder; base; behavior prediction; child well being; cost; cost effective; design; disorder prevention; dosage; effective therapy; flexibility; functional disability; gaze; improved; mathematical model; new technology; novel; public health emergency; real world application; response; sensor; skills; social; social communication; success; therapy design; tool; virtual reality

DESCRIPTION (provided by applicant): It is estimated that 1 in 110 children in the United States are affected by Autism Spectrum Disorders (ASD). The identification and effective treatment of ASD is often characterized as a public health emergency incurring a $35-90 billion annual cost. Traditional interventions designed to address higher level social and adaptive impairments have been demonstrated to be minimally effective for school-aged children and adolescents with ASD and are thought to be a result of a failure of traditional methodologies to systematically match intervention strategies to specific skill deficits within and across naturalistic settings in appropriately intensive dosages. In this grant proposal, in an attempt to address the above concerns, a research plan is developed to apply intelligent adaptive technology as a Virtual Reality (VR) based intervention modality for treatment of a) core social deficits and b) applied adaptive behavioral skills for children and adolescents with ASD. The technology will be applied with capacities for controllable levels of difficulty that can be adapted with the VR environment into both social and adaptive behavioral intervention scenarios in real-time based on predictions of behavioral engagement of participants while engaged with the tasks. Behavioral engagement is operationalized by affective and attentive states and as such, the intervention technology will be sensitive to how variations in an individual child's engagement predict task performance. Rule-governed adaptation will be incorporated into VR interactions and examined explicitly in terms of how such modifications improve performance. Simply, this technology will be applied to automatically adjust task characteristics based on an individual's unique profile in hopes that task performance within core domains of impairment will be greatly bolstered by application of individually modulated and scaffolded reinforcement modalities. The specific aims of this research are: 1) to refine the intelligent adaptive response technology that the authors have already developed in their pilot work, and design both adaptive behavior and social tasks in a VR environment; 2) to develop physiology-based individualized affective models and attention inference mechanisms from eye gaze information, and to design a rule-based supervisor to allow adaptive reinforcement strategies sensitive to behavioral engagement; and 3) to apply and examine the efficacy of prediction models and the adaptive technology in children with ASD relative to improving specific learning related to VR-based and realistic social and adaptive tasks. The success of such an adaptive response technology in ASD intervention will pave the way for systematic exploration and application of adaptive intervention paradigms aimed at matching individual deficit with targeted intervention. PUBLIC HEALTH RELEVANCE: The project will apply and examine the efficacy of a novel adaptive virtual reality (VR) technology as a potential intervention tool for children and adolescents with Autism Spectrum Disorders (ASD). The proposed technology is designed as an 'intelligent' system that automatically adjusts intervention tasks based on physiological data, information about where the child is looking (e.g., eye tracking), and how well the child is performing, in order to enhance performance on tasks that have real-world application. It is believed that the successful application of this new technology has the potential to usher in a new era of personalized, targeted computer-based ASD intervention capable of addressing the core deficits of the disorder in a manner that is more efficacious and accessible.

描述（由申请人提供）：据估计，美国每110名儿童中就有1名受到自闭症谱系障碍（ASD）的影响。ASD的识别和有效治疗通常被描述为公共卫生紧急事件，每年花费350 - 900亿美元。旨在解决更高层次的社会和适应性障碍的传统干预措施已被证明对患有ASD的学龄儿童和青少年的有效性最低，并且被认为是传统方法失败的结果，无法以适当的密集剂量将干预策略系统地与自然环境中的特定技能缺陷相匹配。在这项拨款申请中，为了解决上述问题，开发了一项研究计划，将智能自适应技术作为基于虚拟现实（VR）的干预方式，用于治疗患有ASD的儿童和青少年的a）核心社会缺陷和B）应用自适应行为技能。该技术将具有可控难度水平的能力，可以根据参与者在参与任务时的行为参与预测，实时适应VR环境的社交和自适应行为干预场景。行为参与是可操作的情感和注意力状态，因此，干预技术将是敏感的变化，在一个单独的孩子的参与预测任务的表现。规则控制的适应将被纳入VR交互中，并明确检查这些修改如何提高性能。简单地说，这项技术将被应用于自动调整任务特征的基础上，个人的独特的配置文件，希望在核心领域的损害的任务性能将大大加强应用程序的个别调制和支架加固方式。本研究的具体目标是：1）完善作者在试点工作中已经开发的智能自适应反应技术，并在VR环境中设计适应行为和社会任务; 2）发展基于生理学的个体化情感模型和基于眼睛注视信息的注意推理机制，并设计一个基于规则的监督者，以允许对行为参与敏感的自适应强化策略;和3）应用和检查预测模型和自适应技术在ASD儿童中相对于改善与VR相关的特定学习的功效-基于现实的社会和适应性任务。这种适应性反应技术在ASD干预中的成功将为系统探索和应用适应性干预范例铺平道路，这些干预范例旨在将个体缺陷与有针对性的干预相匹配。 公共卫生关系：该项目将应用并研究一种新型自适应虚拟现实（VR）技术作为自闭症谱系障碍（ASD）儿童和青少年的潜在干预工具的有效性。所提出的技术被设计为一种“智能”系统，该系统基于生理数据、关于儿童正在看哪里的信息（例如，眼动跟踪）以及儿童的表现如何，以便增强具有现实世界应用的任务的表现。据信，这项新技术的成功应用有可能开创一个个性化的、有针对性的、基于计算机的ASD干预的新时代，能够以更有效和更容易获得的方式解决该疾病的核心缺陷。