RIPPLE: Scalable medical telemetry system for supporting combat rescue

Adam Renner, Robert L. Williams, M. McCartney, Brandon Harmon, Lucas Boswell, Subhashini Ganapathy, Kushal Abhyankar, J. West, N. Weiner, Nathan Weinle
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引用次数: 7

Abstract

Emergency response operations would universally benefit by extending telemedicine to the most difficult and challenging environments. For example, the Air Force Pararescue Jumpers (PJ) and Combat Rescue Officers (CRO) perform rescue and life-saving measure in austere environments. Currently, Bluetooth® aided pen-and-paper systems are employed to collect and store medical data, from the time it is sensed to its dissemination. This is proving to be tedious and non-scalable, especially when the number of casualties is larger than the number of responders in a given mission. Pararescue Jumpers, Combat Rescue Officers and similar medical rescue agencies are seeking medical vital sign sensors and telemetry solutions for mass casualty responses in which a small team of medical rescuers must be able to rescue and sustain the life of multiple casualties in critical condition. Project Ripple, to be described in this paper, is meant to create a Medical Body Area Network (MBAN) of sensors to assist in triage and general physiological data collection in a disaster scenario. The system is demonstrates an improved alternative to existing Bluetooth® and pen-and-paper systems by streamlining the processes of data collection, storage, transfer, and visualization. Low-power, wireless devices that utilized open standards makeup the sensor network while custom mobile applications were used for the visualization of the sensor data. Also, flexible and generic sensor fusion architecture is being explored.
RIPPLE:支持战斗救援的可扩展医疗遥测系统
通过将远程医疗扩展到最困难和最具挑战性的环境,应急行动将普遍受益。例如,空军跳伞跳伞员(PJ)和战斗救援人员(CRO)在严峻的环境中执行救援和救生措施。目前,蓝牙辅助笔和纸系统被用于收集和存储医疗数据,从它被感知的时间到它的传播。事实证明,这是乏味且不可扩展的,尤其是在特定任务中伤亡人数大于反应人数的情况下。跳伞伞兵、战斗救援人员和类似的医疗救援机构正在寻求医疗生命体征传感器和遥测解决方案,以应对大规模伤亡,其中一小群医疗救援人员必须能够在危急情况下拯救并维持多名伤亡人员的生命。本文所描述的Ripple项目旨在创建一个由传感器组成的医疗机构区域网络(MBAN),以协助在灾难场景中进行分类和一般生理数据收集。该系统通过简化数据收集、存储、传输和可视化过程,展示了现有蓝牙®和笔和纸系统的改进替代方案。利用开放标准的低功耗无线设备构成了传感器网络,而定制的移动应用程序则用于传感器数据的可视化。同时,还在探索灵活通用的传感器融合架构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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