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

在新冠肺炎大流行期间，加拿大医疗系统内的呼吸机短缺已成为一个直接令人担忧的问题。对于新出现的对额外呼吸机容量的需求，一种解决方案是在多个患者之间共享一个呼吸机，称为多次通风。这一战略已在纽约使用，并已获得卫生与公众服务部和联邦药物管理局的危机批准。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，多重通风系统在主要医疗机构的使用受到了限制。 这项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，以扩大呼吸机的能力。低成本、高效的差动式多重通风(DMV)系统使我们能够利用限流器、传感器和允许调整和监控吸气和呼气参数的控制器，为共享呼吸机的患者提供个性化设置。DMV系统由3D打印可调正端呼气压力(PEEP)阀组成，可以成为一种节省成本、配置灵活的多维替代方案。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的容量，降低生产成本，并提供比传统系统更高质量的患者护理。 这项研究的拟议目标是了解系统的流体动力学，并改进通风系统目前的结构性挑战。该项目的创新之处在于车管所设计参数的分析、遗传算法的优化、微电子机械系统(MEMS)传感器的应用、预补偿算法和物理模型。该提案的结果还提供了配置指南、监控模块和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.