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（由申请人提供）：自闭症的早期发现导致早期治疗，这被证明对结果有重大影响。尽管最近在早期自闭症谱系障碍（ASD）检测方面取得了进展，但美国的平均诊断年龄仍然在5岁左右。ASD诊断目前通过行为评估进行，这需要高度专业化的培训，在农村地区并不普遍，并且可能不一致。对行为评估管理的专门培训的需要和个体评估中涉及的努力排除了这些诊断方法在诊所和儿科医生办公室以及大规模人口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一项早期检测研究，旨在评估ASD家族高危婴儿的行为和大脑发育。行为评估包括对粗大运动功能的专门观察，这是一个在生命的第一年特别突出的发展领域。这项研究沿着其他研究，强调非典型运动发育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/评分个体受试者是一个时间密集、主观的过程，并且需要大量的培训才能实现。 可靠性我们将建立一个人类动作识别引擎（HARE），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-添加一个显着更有效和标准化的方法，以增强当前的诊断护理标准。在第一阶段，我们将：1。开发HARE原型：感兴趣对象的自动分割; 3D取向的确定;从IBIS行为评估组中定义的预定义集合中提取用于动作分类的特征; 2.利用AR引擎的中间输出建立技术，以检测和去识别视频中多个密切互动的人类主体的面部，以进一步处理和数据共享; 3.探索早期标记，根据检测到的动作将受试者分类为ASD和非ASD组，并评估分类引擎的灵敏度和特异性。第一阶段的工作将为从HARE的动作识别输出中创建一个带有动作注释的视频库铺平道路。该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的数据源。最后，HARE系统可以系统地识别新的，以前未识别的运动动作，这些动作可能与以后发育困难，特别是ASD的风险增加有关。这些新的早期风险标志物-结合现有的评估-将允许可靠，早期识别ASD。