CAREER: Beyond Telemedicine: Realizing a Proactive Home Health Care Delivery Model Through Research and Education in Plug-and-Play Components and Novel Sensors

研究和教育计划的总体目标是为家庭设计基于组件的患者监护技术。为了实现这一目标，首席研究员（PI）将创建一个新的医疗组件设计实验室，该实验室将作为一个双向管道，将研究项目和一系列密切相关的工程课程之间的经验教训汇集起来。基于光的传感器已被选为初始车辆，以展示对不同患者数据的连续和不显眼的监测。这个双管齐下的计划将针对（1）在分布式医疗信息基础设施中发挥作用的智能，即插即用的软件和硬件组件的设计，以及（2）开发新型的基于光的移动传感器，可以从患者那里获取有意义的生理数据。具体技术目标包括：1）为基于家庭的监控系统开发安全的分布式基础设施，该基础设施利用即插即用组件互操作性标准，2）构建支持家庭中智能医疗设备操作的硬件/软件组件，3）演示医疗设备与电子病历之间的安全交互，4）创建并临床验证用于从用可穿戴的、所有者感知的、基于光的传感器获取的连续生理数据中提取诊断参数的新算法，五是运用研究方法，利用连续的生理数据来确定和预测健康状况。

The overall goal of the research and education program is to design component-based patient monitoring technologies for the home. To realize this goal, the principal investigator (PI) will create a new Medical Component Design Laboratory, which will function as a bi-directional conduit to funnel lessons learned between research projects and a set of closely related engineering courses. Light-based sensors have been chosen as the initial vehicle to demonstrate continuous and unobtrusive monitoring of diverse patient data. The two-pronged program will target (1) the design of smart, plug-and-play software and hardware components that function within a distributed medical information infrastructure, and (2) the development of novel, light-based ambulatory sensors that can acquire meaningful physiological data from a patient. Specific technical objectives include: 1) develop a secure, distributed infrastructure for home-based monitoring systems that utilizes plug-and-play component interoperability standards, 2) build hardware/software components that support smart medical device operation in the home, 3) demonstrate secure interaction between medical devices and electronic patient records, 4) create and clinically validate new algorithms for extracting diagnostic parameters from continuous physiological data acquired with wearable, owner-aware, light-based sensors, and 5) apply research methods for using continuous physiological data to determine and predict state of health.