A low-cost, effective Differential Multi-Ventilation system for use against COVID-19

在COVID-19大流行期间，加拿大医疗系统内的呼吸机短缺已成为一个迫在眉睫的问题。对于新出现的对额外呼吸机容量的需求的一种解决方案是在多个患者之间共享呼吸机，称为多通气。这一策略已在纽约使用，并获得了卫生与公众服务部和联邦药品管理局的危机批准。然而，由于潜在的安全风险，如共用呼吸机的患者之间的触发问题，多通气系统已被限制在主要医疗机构中使用。 该研究项目提出了一种最先进的系统，使我们能够克服可能的安全风险，以扩大呼吸机容量。低成本和有效的差分多通气（DMV）系统允许我们允许通过利用流量限制器，传感器和控制器，允许吸气和呼气参数的调整和监测共享呼吸机的患者的个性化设置。DMV系统由3D打印的可调节呼气末正压（PEEP）阀门组成，可以成为一种节省成本、配置灵活、多维的替代方案。与传统系统相比，将可调PEEP阀与传感器、旁路电路和控制器相结合，将使我们能够增加呼吸机容量，降低生产成本，并提供更高质量的患者护理。 本研究的目标是了解系统的流体动力学，并改善通风系统目前的结构挑战。该项目的新颖之处在于DMV的设计参数的分析，使用遗传算法的优化，微机电系统（MEMS）传感器的应用，预补偿算法，和物理模型。该方案的成果还提供了一个配置指南，一个监测和控制模块，和DMV动态仿真软件。

Ventilator shortages within Canada's healthcare system have become a problem of immediate concern during the COVID-19 pandemic. One solution for the emerging need for additional ventilator capacity is to share a ventilator between multiple patients, called multi-ventilation. This strategy has been used in New York and has received crisis approval by Health and Human Services and the Federal Drug Administration. However, the multi-ventilation system has been restricted for use in major medical organizations due to potential safety risks such as trigger issues between the patients sharing a ventilator. This research project proposes a state-of-art system that enables us to overcome possible safety risks to expand ventilator capacity. A low-cost and effective Differential Multi-Ventilation (DMV) system allows us to permit individualized settings for patients sharing a ventilator by utilizing flow restrictors, sensors, and a controller that allows adjustment and monitoring of inspiratory and expiratory parameters. The DMV system, which consists of 3D-printed adjustable Positive End-Expiratory Pressure (PEEP) valves, can be a cost-saving, configuration-flexible, multi-dimensional alternative. Combining adjustable PEEP valves with sensors, bypass circuits, and a controller will allow us to increase ventilator capacity, reduce the production cost, and provide improved quality patient care compared to the traditional system. The proposed objectives of this research are to understand the system's fluid dynamics and to improve upon the ventilations' current structural challenges. This project's novelties lie in the analysis of the DMV's design parameters, optimization using a genetic algorithm, the application of micro-electromechanical system (MEMS) sensors, a pre-compensation algorithm, and the physical model. This proposal's outcome also provides a configuration guideline, a monitoring and control module, and DMV dynamic simulation software.