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用于出血战斗伤员远程分诊应用的先进技术开发。

Advanced technology development for remote triage applications in bleeding combat casualties.

作者信息

Ryan Kathy L, Rickards Caroline A, Hinojosa-Laborde Carmen, Gerhardt Robert T, Cain Jeffrey, Convertino Victor A

机构信息

US Army Institute of Surgical Research, Fort Sam Houston, TX, USA.

出版信息

US Army Med Dep J. 2011 Apr-Jun:61-72.

Abstract

Combat developers within the Army have envisioned development of a "wear-and-forget" physiological status monitor (PSM) that will enhance far forward capabilities for assessment of Warrior readiness for battle, as well as for remote triage, diagnosis and decision-making once Soldiers are injured. This paper will review recent work testing remote triage system prototypes in both the laboratory and during field exercises. Current PSM prototypes measure the electrocardiogram and respiration, but we have shown that information derived from these measurements alone will not be suited for specific, accurate triage of combat injuries. Because of this, we have suggested that development of a capability to provide a metric of circulating blood volume status is required for remote triage. Recently, volume status has been successfully modeled using low-level physiological signals obtained from wearable devices as input to machine-learning algorithms; these algorithms are already able to discriminate between a state of physical activity (common in combat) and that of central hypovolemia, and thus show promise for use in wearable remote triage devices.

摘要

陆军中的作战研发人员设想开发一种“即用即忘”的生理状态监测器(PSM),这将增强在前沿地区评估士兵战斗准备状态的能力,以及在士兵受伤后进行远程分诊、诊断和决策的能力。本文将回顾近期在实验室和野外演习中测试远程分诊系统原型的工作。目前的PSM原型可测量心电图和呼吸,但我们已经表明,仅从这些测量中获得的信息并不适合对战斗损伤进行特定、准确的分诊。因此,我们建议开发一种能够提供循环血容量状态指标的能力,以用于远程分诊。最近,已经成功地利用从可穿戴设备获得的低水平生理信号作为机器学习算法的输入,对血容量状态进行了建模;这些算法已经能够区分身体活动状态(在战斗中常见)和中心性低血容量状态,因此在可穿戴远程分诊设备中的应用前景广阔。

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