HARE: Action Recognition System for Behavioral Assessment Training, Data-sharing, and Early Markers Detection for Autism Spectrum Disorders.

HARE：用于自闭症谱系障碍行为评估培训、数据共享和早期标记检测的动作识别系统。

• 批准号: 9247734
• 负责人: BHARATH MODAYUR
• 金额: $ 4万
• 依托单位: BSOLUTIONS, INC.
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-20 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9247734
• 关键词: Age; Age-Months; Alberta province; Archives; Area; Attention; Autistic Disorder; Beds; Behavior assessment; Behavioral; Brain; Brain imaging; Classification; Clinic; Clinical; Code; Computer Vision Systems; Computer-Assisted Image Analysis; Data; Data Set; Detection; Development; Diagnosis; Diagnostic; Diagnostic Procedure; Early Diagnosis; Early identification; Early treatment; Face; Goals; Head; Health; Human; Individual; Infant; Learning; Life; Measures; Methodology; Methods; Motor; Movement; Outcome; Output; Phase; Physiology; Population; Process; Reaction Time; Research; Resources; Risk; Risk Marker; Savings; Sensitivity and Specificity; Services; Siblings; Source; Standardization; Symptoms; System; Techniques; Testing; Time; Training; Universities; Washington; Work; autism spectrum disorder; base; commercialization; computerized data processing; cost effective; data sharing; design; early detection biomarkers; high risk infant; human subject; improved; infancy; interest; neurobehavioral; novel; pediatrician; prototype; repetitive behavior; repository; rural area; screening; social communication; standard of care; tool

 DESCRIPTION (provided by applicant): Early detection of autism leads to earlier treatment, which is proven to have a major impact on outcomes. In spite of recent advances in early Autism Spectrum Disorders (ASD) detection, the average age of diagnosis in the US is still around five. ASD diagnosis is currently performed via behavioral assessment, which requires highly specialized training, is not widely available in rural areas, and may be applied inconsistently. The need for specialized training for the administration of behavioral assessment and the effort involved in individual assessments preclude large scale deployment of these diagnostic methods in clinics and pediatricians' offices as well as large scale population studies. The Infant Brain Imaging Study (IBIS) is an early detection study at the University of Washington Autism Center which assesses behavioral and brain development in infants at high familial risk for ASD. Behavioral assessments include specialized observations of gross motor function, an area of development that is uniquely highlighted in the first year of life. This study along with others, highlight atypical motor development as the first step in the emergence of autism-related symptoms. Analyzing behavioral video data in order to assess/score individual subjects is a process that is time-intensive, subjective, and requires extensive training to attain reliability. We will build a Human Action Recognition Engine (HARE) that leverages computer vision tools to automatically extract, quantify and classify known motor actions - from video datasets - adding a significantly more efficient and standardized method to augment the current diagnostic standard of care. In this Phase I proposal, we will: 1. Develop the HARE prototype: automatic segmentation of subject of interest; determination of 3D orientation; extraction of features that are used in classification of actions from a predefined set defined in the IBIS behavioral assessment battery; 2. Leverage the intermediate outputs of the AR engine in establishing techniques to detect and de-identify faces of multiple, closely-interacting human subjects in video toward further processing and data sharing; 3. Explore early markers to classify subjects, based on actions detected, into ASD and non-ASD groups and evaluate the sensitivity and specificity of the classification engine. This Phase I effort will pave the way forthe creation of an action-annotated video repository from HARE's action recognition output. The repository will provide a rich source of highly-accessible data toward training and further research discoveries. Finally, the HARE system can systematically identify new, previously unidentified motor actions that may relate to increased risk for later developmental difficulties, particularly ASD. These novel early risk markers - in combination with existing assessments - would allow reliable, earlier identification of ASD.

 描述（适用提供）：早期发现自闭症会导致早期治疗，事实证明，这对结果产生了重大影响。尽管早期自闭症谱系障碍（ASD）的最新进展，但美国诊断的平均年龄仍大约五个。目前，ASD诊断是通过行为评估进行的，该行为评估需要高度专业化的培训，在农村地区不广泛使用，并且可能不一致地应用。对行为评估进行专门培训的需求以及参与个人评估的努力排除了这些诊断方法在诊所和儿科医生的办公室以及大规模的人群研究中的大规模部署。 婴儿脑成像研究（IBIS）是华盛顿大学自闭症中心的早期探测研究，评估了ASD高家庭风险的婴儿的行为和大脑发育。行为评估包括对总体运动功能的专业观察，这是一个生命第一年的发展领域。这项研究与其他研究强调了非典型运动发展是自闭症相关症状出现的第一步。分析行为视频数据以评估/分数个体主题是一个时间密集型，主观的过程，并且需要大量的培训才能获得 可靠性。我们将构建人类动作识别引擎（野兔），该引擎利用计算机视觉工具自动提取，量化和分类已知的运动动作 - 从视频数据集中 - 添加了一种更有效和标准化的方法来增强当前的诊断护理标准。在此阶段的建议中，我们将：1。开发野兔原型：自动分割感兴趣的主题；确定3D方向；提取用于分类的功能，从宜本行为评估电池中定义的预定义集合中进行分类； 2。利用AR发动机的中间输出建立技术来检测和识别视频中多个，紧密相互关联的人类受试者的面孔，以进一步处理和数据共享； 3。探索早期标记，以根据检测到的动作分类为ASD和非ASD组，并评估分类引擎的敏感性和特异性。这一阶段I的努力将为Hare的动作识别输出创建一个动作声明的视频存储库铺平道路。存储库将为培训和进一步的研究发现提供丰富的高度可访问数据来源。最后，野兔系统可以系统地确定新的，以前未知的运动动作，这可能与以后发育困难（尤其是ASD）的风险增加有关。这些新型的早期风险标记 - 结合现有评估 - 将允许可靠的，更早地识别ASD。