Integrating & Visualizing Clinical, Environmental, and Sensor Data

项目2摘要（项目说明） 背景和可用性是生物医学实时健康评估设计背后的重要驱动因素， 儿童哮喘（呼吸）平台。首先，没有上下文，很难理解数据上限- 由传感器捕获，减少了观测的效用。这一观察促使BREATHE将其作为 关于患者及其情况和周围环境的许多信息，以便充分地情境化解释， 并提出明智的建议。第二，可用性是移动的健康领域的一个必须考虑的因素 （mHealth）：如果系统被认为无法使用-无论出于何种原因-患者将无法依从， mHealth应用程序最终会失败。这两个想法激发了项目2，它开发了信息基础设施， 一种结构，用于围绕感测到的数据启用上下文，分析数据，并优化交互范围 和活动不同的用户将与呼吸。 项目2从开发一个统一的、可扩展的儿童哮喘数据模型开始， 标准化和组织信息的基础。数据模型创建了一个全面的视图， 不同类型的感知信息（生理、环境）、临床信息和自我报告信息， 信息（例如，症状），都随着时间的推移而累积。给定这个数据模型，项目2建立了一个信息 支持新数据源的体系结构（例如，实时空气质量报告，电子健康记录）， 与传感器数据相结合，提供额外的上下文。开放源码项目（UIMA，Taverna）适用于 提供一个灵活的框架，用于指定数据收集协议和相关的数据处理工作流程 这些综合数据集。作为一个用例，处理工作流与统计和机器的链接 学习方法，以帮助预测风险建模哮喘急性发作被认为是沿着支持 进行实时分析，以促进BREATHE系统的及时响应。最后，统一数据 模型还支持创建一系列用户界面（UI）和可视化：利用ohmage， 引导移动终端客户端和UI开发，包括部署预定的调查，提醒， 和数据收集;建议使用基于网络的用户界面，以支持审查数据收集协议， 患者特定的时间轴视图，使临床医生和研究人员能够“深入”收集信息。 通过仔细的需求分析，可用性问题反映在这些不同UI的开发中， 迭代设计和测试。在这方面，项目2与项目1密切合作， 移动终端接口，并与项目3一起收集关于系统设计和可用性的反馈，以便改进 在该中心的努力过程中，该平台。

PROJECT 2 ABSTRACT (PROJECT DESCRIPTION) Context and usability are important drivers behind the design of the Biomedical REAl-Time Health Evaluation for Pediatric Asthma (BREATHE) platform. First, without context, it becomes difficult to understand the data cap- tured by sensors, diminishing the utility of observations. This observation spurs BREATHE to incorporate as much information about a patient and his/her situation and surroundings in order to fully contextualize interpre- tations and make informed recommendations. Second, usability is an imperative consideration in mobile health (mHealth): if the system is perceived as unusable – for any reason – patients will fail to be compliant and the mHealth application will ultimately fail. These two ideas motivate Project 2, which develops the informatics infra- structure to enable context around sensed data, to analyze the data, and to optimize the range of interactions and activities different users will have with BREATHE. Project 2 starts with development of a unified, extensible data model for pediatric asthma, establishing a common foundation for standardizing and organizing information. The data model creates a comprehensive view across different types of sensed information (physiologic, environmental), clinical information, and self-reported infor- mation (e.g., symptoms), all accrued over time. Given this data model, Project 2 establishes an information architecture that enables new data sources (e.g., real-time air quality reports, electronic health records) to be combined with sensor data, providing additional context. Open source projects (UIMA, Taverna) are adapted to provide a flexible framework for specifying data collection protocols and associated data processing workflows on these integrated datasets. As a use case, the linkage of processing workflows to statistical and machine learning methods to aid in predictive risk modeling of asthma exacerbations is considered, along with support for real-time analytics in order to facilitate timely responses by the BREATHE system. Finally, the unified data model also enables the creation of a range of user interfaces (UI) and visualizations: ohmage is leveraged to bootstrap mobile device client and UI development, including the deployment of scheduled surveys, reminders, and data collection; and web-based UIs are proposed to support the review of data collection protocols and patient-specific timeline views that enable clinicians and researchers to “drill down” into collected information. Usability concerns are reflected in the development of these various UIs through careful requirements analysis, and iterative design and testing. In this regard, Project 2 works closely with Project 1 to develop BREATHE’s mobile device interfaces, and with Project 3 to garner feedback on system design and usability in order to refine the platform over the course of the Center’s efforts.