I-Corps: Translation potential of a semi-autonomous feedback device to enable manual ventilation

这个i-Corps项目专注于开发一种能够正确执行手动通风的医疗设备。在COVID大流行的高峰期，许多人都是手工通风的，这一程序的技能似乎高度不同，这对患者来说是一个重大风险。这项技术既可用作医疗器械，也可用作评估装置和教学工具。其目标是通过改善危重医疗情况下的培训、护理和结果来应对肺部、急救和危重护理医学方面的挑战，并加强医疗保健实践。该设备记录和传输实时代谢信息，有望推动医疗技术和患者结果的进步。此外，该设备可以用作紧急医疗服务(EMS)和其他医务人员的培训工具，这可能会将技能损失降至最低，并降低患者风险。这个i-Corps项目利用体验式学习和对行业生态系统的第一手调查来评估该技术的翻译潜力。这个解决方案的基础是开发一种生理/代谢监测器。这项技术结合了一个高灵敏度的流量计、压力传感器和二氧化碳(CO2)测量电路，以及一个基于计算机的翻译器，可以激活光环和扬声器系统。该方案为用户提供了多种形式的反馈，简单有效。一旦使用开关根据患者的大小进行编程来选择个人特征，该设备就会使用一组特殊的流量和压力算法来指定何时提供呼吸以及提供多大程度的呼吸。该设备还根据呼出的二氧化碳监测患者的代谢状态。此外，培训计划是这项技术的核心组成部分，已被证明可以提高技能。这些结果显示了对医疗技术和患者结果产生积极影响的潜力。这一奖项反映了NSF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。

This I-Corps project focuses on the development of a medical device that enables the correct performance of manual ventilation. During the height of the COVID pandemic, many individuals were hand ventilated and the skills for this procedure appeared to be highly variable, which is a significant risk for patients. This technology may be used as both a medical device, and an evaluation device and teaching tool. The goal is to address challenges in pulmonary, emergency, and critical care medicine and enhance healthcare practices by improving training, care, and outcomes in critical medical situations. The device records and transmits real-time metabolic information, promising advancements in healthcare technology and patient outcomes. In addition, the device may be used as a training tool for emergency medical services (EMS) and other medical personnel, which may minimize skill loss and reduce patient risk. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of a physiologic/metabolic monitor. The technology incorporates a high sensitivity flow meter and pressure sensor and carbon dioxide (CO2) measuring circuit with a computer-based interpreter that activates a light ring and speaker system. This solution provides several forms of feedback to the user, which is simple and effective. Once programmed for a patient’s size using a switch to select individual characteristics, the device uses a special set of flow and pressure algorithms to specify when and to what extent breaths are provided. The device also monitors the patients' metabolic states based on CO2 exhaled. In addition, a training program is a core component of the technology and has been shown to improve skills. These results show potential for positive impacts on healthcare technology and patient outcomes.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.