MRI: Development of a Next-Generation Multimodal Data Management Human-Sensing Instrument for Trustworthy Research Collaboration and Quality of Life Improvement

提案编号：CNS 09-23494 主要研究者：Makedon，Fillia S.; Athitsos，Vassilis; Huang，Heng; Le，Zhengyi; Popa，Dan O.机构：德克萨斯大学-阿灵顿分校标题：MRI/开发：下一代多模态数据管理人感仪 值得信赖的研究合作和生活质量改善项目建议：本项目开发一种仪器，作为一个互动的个人护理和人类活动监测中心，旨在保持一个人的高质量生活和安全，尽可能长的时间在家里。该仪器通过与辅助生活环境中的远程用户的无线连接实现隐私保护和安全数据共享。zooscopion（zScope）提供精神和情感支持，可以连接设备、人类、物体和环境。它可以连接到其他辅助生活项目，使它们具有互操作性，并可以提供具有高教育和培训价值的净化研究数据和案例的数字图书馆。zScope将多种类型的数据进行组合和关联，并提取指示变化、风险等的感兴趣事件。它可以分析面部表情以检测疼痛、环境数据、房屋数据（如开门、电话声、吸尘器等），人的表现度量（例如，手的力量），以连续和离散的格式。以有意义的方式对数据进行建模和组装，以预测和防止物理和数字问题（例如，分别为福尔斯和侵入）。隐私和安全性在设计阶段就成为数据建模的一部分。该仪器将采集传感器数据、人体测量数据、相机数据（应要求）、其他病例的已知行为模式、脑部扫描和临床信息，旨在提供纵向和偶发事件的高分辨率显示。它输出在辅助环境中有价值的模式和重要人类行为“事件”的视觉交互显示，设置在哪里使用非侵入性监测技术，帮助识别“行为生物标志物”，这些生物标志物将与其他类型的健康指标相关联，这些健康指标可能来自大脑成像，遗传分析，临床结果或心理评估。它将与下一代数据一起工作，包括行为，临床，身体运动等，并且具有低延迟跟踪。更广泛的影响：这项工作实现了以人为中心的实验类型，并提供了新颖的交互，可视化和安全协作的新方式。为老年人开发“更智能”的生活环境为教育开辟了新的途径，这些项目具有身临其境的吸引力，可以更好地了解科学和工程在将健康数据（基因组信息）与行为相结合时的作用，预测趋势，并提供药物和临床评估如何与纵向行为联系的指标。长期目标包括评估环境，药物和人类心理融合的行为标记。预计该工具还将回答有关对所收集信息进行新分析的新需求的询问。它包括带有搜索和浏览工具的培训和教育模块，以及支持决策和使用存储策略的推荐工具。此外，利用现有的外展计划，该项目将支持当地少数族裔学生和高中生。能够跨越领域孤岛共同努力实现以人为本的目标的新一代科学家可能正在形成！

Proposal #: CNS 09-23494 PI(s): Makedon, Fillia S.; Athitsos, Vassilis; Huang, Heng; Le, Zhengyi; Popa, Dan O.Institution: University of Texas - ArlingtonTitle: MRI/Dev.: Next Generation Multimodal Data Management Human-Sensing Instrument for Trustworthy Research Collaboration and Quality of Life ImprovementProject Proposed:This project, developing an instrument that serves as an interactive personal care and human activity monitoring center, aims to keep a person with high quality life and safe at home as long as possible. The instrument enables privacy-preserving and secure data sharing through wireless connection with remote users in an assistive living environment. Providing mental and emotional support, the zooscopion (zScope) can connect devices, humans, objects, and the environment. It can connect to other assistive living projects, making them interoperable and can deliver a Digital Library of sanitized research data and cases with high educational and training value. zScope combines and correlates many types of data and extracts events of interest that indicate changes, risks, etc. It can analyze facial expressions to detect pain, environmental data, house data (such as door opening, telephone sounds, vacuum cleaner, etc.), human performance metrics (e.g., hand strength), both in continuous and discrete format. Data are modeled and assembled in meaningful ways to predict and prevent physical and digital problems (e.g., respectively, falls and intrusions). Privacy and security are being made part of the data modeling at the design phase. The instrument will take sensor data, human body measurements, camera data when requested, known pattern of behavior from other cases, brain scans, and clinical information, aiming to provide high resolution displays of longitudinal as well as episodic events. It outputs a visual interactive display of patterns and significant human behavioral 'events' valuable in assistive environments, setting where to use non-invasive monitoring technologies, helping recognize 'behavioral biomarkers' that will be connected to other types of health indicators that may come from brain imaging, genetic analysis, clinical results, or psychological evaluations. It will work with the next generation of data that include behavioral, clinical, body motion, etc., and have low latency tracking. Broader Impacts: This work enables human-centric type of experiments and provides novel new ways of interaction, visualization, and secure collaboration. Developing 'smarter' living environments for the aged opens new ways to education with immersive compelling projects that provide a better understanding of the role of science and engineering when combining health data (genomic information) to behavior, predict trends, and provide indicators of how medication and clinical assessments connect to longitudinal behavior. Long term goals include behavioral markers for assessing the confluence of environment, drugs, and human psychology. The instrument is also expected to respond to queries regarding emerging needs for new analysis of collected information. It includes training and educational modules with search and browsing tools and a recommender facility to support decision making and use stored strategies. Moreover, utilizing existing outreach programs, the project will support local minority students and high school students A new generation of scientists that can work together across domain silos towards human centered goals might be in the making!