SCH: EXP: Collaborative Research: Design of a wearable biosensor system with wireless network for the remote detection of life threatening events in neonates

在美国，每八个婴儿中就有一个是早产儿。这些高危婴儿不仅需要在新生儿重症监护室（NICU），而且需要在家庭环境中对其生理进行专门监测。他们容易出现呼吸暂停（呼吸暂停）、心动过缓（心脏缓慢）和缺氧（氧不饱和），这些都是危及生命的。本项目旨在开发一种具有无线网络的生物传感器系统，用于远程检测和预测婴儿的此类生命威胁事件。拟议的研究超越了传统的健康监测系统，将身体传感器网络（BSN）沿着先进的信号处理方法，专门针对个别婴儿的生理，以准确地检测和预测威胁生命的事件的前兆。拟议的研究可以通过无线生物传感器系统对婴儿的非侵入式动态健康监测产生重大影响，该系统将轻量级传感器解决方案集成到用于监测生理的传感，通信和计算中。本计画所开发之系统架构、理论、模型与程式码，可供研究人员与工程师使用，以评估婴儿监护应用之效能。该项目还包括：（1）向学术界和工业界传播项目信息和知识;（2）吸引本科生、研究生和医学生，特别是妇女和少数民族，参与拟议的研究;以及（3）开发新课程和修订现有课程。目前在NICU中使用的生理监测系统由附接到婴儿的相对较大的传感器组成，所述传感器然后通过多根导线连接到数据采集系统。这些传感器沿着导线是临床护理的障碍。此外，由于尺寸和成本，现有系统不能用于家庭环境。虽然NICU监测系统中存在大量生理信号，但对于照顾早产儿的临床医生来说，确定病理状态是一项挑战，因为没有方法可以将这些信号转换为经验证的指标来定义病理。这项拟议研究的主要目标是探索是否可以建立一个专用的紧凑型设备与可穿戴生物传感器沿着与无线网络的检测和预测的婴儿在新生儿重症监护室和家庭环境中的危及生命的事件。第二个目标是探讨是否可以开发提供实时心肺风险指数的计算工具，以协助临床医生进行新生儿护理。具体而言，该项目将开发一个综合系统，包括四个重要组成部分：（1）开发可附在非常小和脆弱的婴儿身上的微型生物传感器;（2）开发具有有效通信协议的无线设备，可传输生物传感器的生理信号;（3）开发有效的信号处理算法，该算法可以从生物传感器数据中提取有用的信息，用于危险分层和预测危及生命的事件（数据到知识到决策）和（4）在NICU的真实的生活环境中测试和验证系统。该项目中提出的方法最终可以导致一种用于远程检测婴儿生命威胁事件的医疗设备，并为一般医疗监测应用的可穿戴无线生物传感器系统的设计提供指导。

In the United States, one in eight infants is born prematurely. These high risk infants require specialized monitoring of their physiology not only in Neonatal Intensive Care Units (NICU) but also in home environments. They are prone to apnea (pause in breathing), bradycardia (slowness of heart) and hypoxia (oxygen de-saturation), which are life threatening. This project aims at developing a biosensor system with wireless network for the remote detection and anticipation of such life threatening events in infants. The proposed research goes beyond traditional health monitoring systems by incorporating body sensor networks (BSN) along with advanced signal processing approaches, tailored specifically to an individual infant's physiology, to accurately detect and anticipate precursors of life threatening events. The proposed research can have a significant impact on non-intrusive ambulatory health monitoring for infants through a wireless biosensor system that integrates lightweight sensor solutions into the sensing, communication, and computing for monitoring physiology. The system framework, theories, models, and code developed by this project can be used by researchers as well as engineers to evaluate the performance of infant monitoring applications. The project also includes: (1) disseminating the project information and knowledge to the academic community and industry; (2) engaging undergraduate, graduate and medical students, especially women and minorities, into the proposed research; and (3) developing new courses and revising the existing courses. The current physiological monitoring systems used in NICU consist of relatively large sensors attached to the infants, which are then connected to a data acquisition system with multiple wires. These sensors along with the wires are a hindrance to the clinical care. In addition, the existing system cannot be used for home environments because of the size and cost. While there is an abundance of physiological signals streaming across NICU monitoring systems, it is challenging for clinicians caring for preterm infants to determine pathological states, as there is no method available to translate these signals into validated indices to define pathology. The primary objective of this proposed research is to explore whether a dedicated compact device with wearable biosensors along with wireless networks can be built for the detection and anticipation of life threatening events in infants in both NICU and home environments. The secondary objective is to explore whether computational tools that provide real-time indices of cardio-respiratory risk can be developed to assist clinicians for neonatal care. Specifically, the project is to develop a comprehensive system, involving four important components: (1) development of miniature biosensors that can be attached to infants who are very small and vulnerable; (2) development of wireless devices with efficient communication protocols that can transmit the physiological signals from the biosensors; (3) development of efficient signal processing algorithms that can extract useful information from the biosensor data for risk stratification and anticipation of life threatening events (data to knowledge to decisions) and (4) testing and validation of the systems in real life environment at NICU. The proposed approaches in the project can eventually lead to a medical device for the remote detection of life threatening events in infants and also provide guidelines for the design of wearable wireless biosensor systems for healthcare monitoring applications in general.