MRI: Development of a Video-Based Robotic Instrument for Behavioral Analysis and Diagnosis of At-Risk Children

建议#：10-39741 Pi(S)：Papanikolopoulos，Nikolaos；Lim，Kelvin；Guillermo Sapiro研究所：明尼苏达大学。标题：核磁共振/开发：基于视频的机器人工具，用于高危儿童的行为分析和诊断项目建议：建议的工具集构成基于视频的机器人工具，其目标是对有精神障碍风险的儿童进行早期诊断。因此，这项提议处于计算机科学、心理学和精神病学以及医学之间的学科边界。有人提议开发一种机器人仪器，可以观察并自动分析儿童的异常情况，从而引入一种新的技术，可以帮助识别处于危险中的儿童。具体活动包括：-开发和临床验证量化儿童精神障碍的仪器和临床方案；-在该仪器中开发和使用计算机视觉和机器学习方法；-开发统计模型以评估现有的相关数据集；-使用广泛的被动和主动传感器以及最先进的3D摄像系统来收集和分析监测的数据；-使用机器人和机器宠物作为检测和治疗精神障碍的手段；以及-在医学院对该仪器进行实际验证。更广泛的影响：最近使用计算机视觉方法/硬件和机器人来检测儿童的精神障碍本身就构成了强大的更广泛的影响。计划中还包括教育项目(研讨会、教程等)。这将使医生和心理学家能够对上述方法/程序进行培训，否则这些方法/程序是不可能的。此外，参与机构的重大计划课程开发都是围绕该文书进行的。此外，还将开展针对代表性不足群体的中学生的外联活动，以及对各种相关患者群体的外联活动。这个真正跨学科的项目还计划包括国际合作伙伴。

Abstract Proposal #: 10-39741 PI(s): Papanikolopoulos, Nikolaos; Lim, Kelvin; Guillermo Sapiro Institution: University of Minnesota Title: MRI/Dev.: Video-Based Robotic Instrument for Behavioral Analysis and Diagnosis of At-Risk Children Project Proposed: The proposed set of tools constitutes a video-based robotic instrument which targets the domain of early diagnosis for children at risk of developing psychiatric disorders. As such, this proposal is at the disciplinary boundaries between computer science, psychology and psychiatry, and medicine. Proposed is the development of a robotic instrument that could observe and automatically analyze abnormalities in children, thus introducing a novel technology which can help identifying children at risk. Specific activities include: - Development and clinical verification of instrumentation and clinical protocols to quantify mental disorders in children; - Development and usage of computer vision and machine learning methodologies in the instrument; - Development of statistical models to evaluate the available related data sets; - Usage of a wide array of passive and active sensors and state-of-the-art 3D camera systems to collect and analyze the monitored data; - Usage of robots and robot pets as a means to detect and treat mental disorders; and, - Practical validation of the instrument at the Medical School. Broader Impacts: The recent usage of computer vision methodologies/hardware and robotics for detection of mental disorders in children, in itself, constitutes strong broader impacts. Planned are also educational programs (workshops, tutorials, etc.) that will enable training gathering of physicians and psychologists to the aforementioned methods/procedures, which would otherwise not be possible. Moreover, significant planned curriculum development at the participating institutions revolves around the instrument. In addition, outreach activities for middle-school students from underrepresented groups will take place, and so will outreach to various pertinent patient groups. This truly interdisciplinary project also plans to include international partners.