RAPID: Open Research Infrastructure for COVID-19 Ventilator Data

肺部是SARS-CoV-2病毒的主要攻击途径。呼吸问题是新冠肺炎的主要症状，早期迹象表明，它的表现与以前的急性呼吸窘迫综合征不同。迫切需要了解如何为需要人工呼吸机的患者提供最佳护理，将死亡率和对存活患者的不良长期影响降至最低。该项目将阐明新冠肺炎压力下的肺功能，并提供开放工具，让更大的社区参与进来，帮助理解这一非常紧迫的社会问题。该项目的成果将包括仪器设备的进步、软件和数据，以及新冠肺炎压力下的肺功能模型。该项目还将向医学界介绍如何治疗新冠肺炎患者，因为新冠肺炎与以前的ARDS患者有明显的不同。呼吸和肺功能从根本上是一个动态的物理系统，服从传统的压力/容量/流量关系，有一个量被称为“肺顺应性”。新冠肺炎是独一无二的，因为潜在的生物学可以导致这个动力系统参数的变化，变化速度惊人，不同于以前的急性呼吸窘迫综合征病例，在几小时或几天的时间尺度上。医务人员需要驾驭病毒感染和机械通风引起的肺部炎症和潜在损伤后果的不断演变的性质，结果从恢复到对疾病后肺功能产生不同影响到死亡。该项目包括三项相关活动：(1)仪器：继续开发低成本、开放来源的呼吸机监测仪，包括可供选择的其他容易获得的部件，以及关于校准的相关文件。(2)数据：与更广泛的社区一起开发呼吸和呼吸机数据的开放数据集，包括流量、压力、氧气水平和衍生的兴趣量，以支持在原本缺乏开放数据的空间进行创新和机器学习。(3)模型：为在新冠肺炎等压力下的机械通风和呼吸过程开发开放的模拟、可视化和模型，使物理学家能够理解系统，促进创新，并有可能帮助医学界。该奖项是使用分配给MP的冠状病毒援助、救济和经济安全(CARE)法案补充条款提供的资金颁发的。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The lungs are a key avenue of attack for the SARS-CoV-2 virus. Respiratory problems are primary symptoms of COVID-19, and early indication is that it does not behave like previous examples of Acute Respiratory Distress Syndrome (ARDS). A severe urgency exists to understand how to provide optimal care for patients requiring artificial ventilation, to minimize both mortality and adverse long-term effects on those patients who survive. The project will illuminate lung function under the stress of COVID-19 and provide open tools to engage the larger community to help understand this very urgent societal problem. The project output will include instrumentation advances, software and data, as well as models of lung function under the stress of COVID-19. The project will also inform the medical community as to how to treat COVID-19 patients, because COVID-19 differs notably from prior experience with ARDS.Respiration and lung function is fundamentally a dynamical physical system amenable to traditional pressure/volume/flow relationships, with a quantity called "lung compliance." COVID-19 is unique, in that the underlying biology can lead to changes in the parameters of this dynamical system that are surprisingly fast, and different from previous ARDS cases, on the time scale of hours or days. Medical personnel need to navigate the evolving nature of the consequences of the viral infection as well as mechanical ventilation induced lung inflammation and potential injury, with outcomes ranging from recovery with varying impacts on post-illness lung function to death. This project consists of three related activities: (1) Instrumentation: Continued development of a low-cost, open-source ventilator monitor, including additional options for readily sourceable parts, and related documentation on calibrations. (2) Data: Development, with the broader community, of open datasets of breathing and ventilator data, including flow, pressure, O2 levels, and derived quantities of interest to enable innovation and machine learning in a space that otherwise lacks open data. (3) Models: Development of open simulations, visualizations, and models for mechanical ventilation and the breathing process, under stresses like COVID-19, that enable a physicist's understanding of the system, enable innovation, and can potentially aid the medical community.This grant is being awarded using funds made available by the Coronavirus Aid, Relief, and Economic Security (CARES) Act supplement allocated to MPS.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.