Inexpensive Multipatient Respiratory Monitoring System for Helmet Ventilation During COVID-19 Pandemic
Inexpensive Multipatient Respiratory Monitoring System for Helmet Ventilation During COVID-19 Pandemic
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DOI：
10.1115/1.4053386
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发表时间：
2022-03-01
影响因子：
0.9
通讯作者：
Tully, Christopher
中科院分区：
文献类型：
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作者：
Bourrianne, Philippe;Chidzik, Stanley;Tully, Christopher
头盔持续正压是一种无创通气（NIV）形式，已用于为COVID-19患者提供呼吸支持。Helmet NIV成本低，容易获得，在患者和临床医生之间提供病毒过滤器，并且可以减少对有创通气的需求。然而，由于缺乏解决已知安全漏洞和监测患者所需的呼吸监测系统，其广泛采用受到限制。为了满足这些安全性和临床需求，我们开发了一种廉价的呼吸监测系统，该系统基于适合本地制造的现成组件。提供开源设计和制造文档。该监测系统包括头盔回路呼气路径上的流量、压力和CO2传感器，以及一个中央远程站，可监测多达20名患者。该系统在台架测试中，在健康志愿者的人类受试者测试中，以及在比较呼气路径处获得的呼吸特征与来自近端传感器的同步地面实况测量的实验中进行了验证。在呼气路径的流量和压力的测量显示在高流速下偏离，并且通过呼气路径报告的潮气量被系统地低估。头盔监测系统表现出高流速，非线性效应的流动和头盔动力学。发现这些偏差在合理范围内，原则上应允许校准、校正和部署临床准确的衍生量。
Helmet continuous positive applied pressure is a form of noninvasive ventilation (NIV) that has been used to provide respiratory support to COVID-19 patients. Helmet NIV is low-cost, readily available, provides viral filters between the patient and clinician, and may reduce the need for invasive ventilation. Its widespread adoption has been limited, however, by the lack of a respiratory monitoring system needed to address known safety vulnerabilities and to monitor patients. To address these safety and clinical needs, we developed an inexpensive respiratory monitoring system based on readily available components suitable for local manufacture. Open-source design and manufacturing documents are provided. The monitoring system comprises flow, pressure, and CO2 sensors on the expiratory path of the helmet circuit and a central remote station to monitor up to 20 patients. The system is validated in bench tests, in human-subject tests on healthy volunteers, and in experiments that compare respiratory features obtained at the expiratory path to simultaneous ground-truth measurements from proximal sensors. Measurements of flow and pressure at the expiratory path are shown to deviate at high flow rates, and the tidal volumes reported via the expiratory path are systematically underestimated. Helmet monitoring systems exhibit high-flow rate, nonlinear effects from flow and helmet dynamics. These deviations are found to be within a reasonable margin and should, in principle, allow for calibration, correction, and deployment of clinically accurate derived quantities.