基于图像的呼吸器尺寸Web应用程序:大流行期间的非接触式口罩安装

Carly L. Donahue, Mu’ath Adlouni, D. Choksi, Brendan D’Souza, Zachary I Richards, R. Sims, IV
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引用次数: 1

摘要

在2019冠状病毒病大流行之初,许多医院和医疗机构缺乏足够的口罩和其他个人防护装备。此外,为确保医护人员拥有适当大小的口罩而制定的协议消耗了宝贵的时间和资源。任何决定用户正确的呼吸器尺寸都需要亲自评估,并且有可能浪费多个呼吸器。在这里,我们介绍IBARS(基于图像的呼吸器尺寸应用程序),这是一个基于面部图像和基本用户人口统计数据提供呼吸器尺寸建议的新工具。该解决方案避免了亲自评估的需要,在几秒钟内提供准确的尺寸建议。该应用程序有可能减少每个工人的呼吸器安装时间,减少总体呼吸器的使用,并通过为医院提供非接触式尺寸选择来提高安全性。此外,未来的应用程序可以通过快速评估和重新评估其工作人员使用的适当呼吸器尺寸来帮助医疗保健机构优化供应链。早期测试表明该软件的准确率为71.3% (N=16),休斯顿卫理公会医院正在进行进一步的测试。
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Image-Based Web Application for Respirator Sizing: Contactless Mask-Fitting During a Pandemic
At the beginning of the COVID-19 pandemic, many hospitals and healthcare institutions lacked an adequate supply of masks and other personal protective equipment. Moreover, protocols that were in place to ensure healthcare workers had appropriately sized masks consumed precious time and resources. Any determination of a user’s correct respirator size demanded an in-person assessment and had the potential to waste multiple respirators. Here we introduce IBARS (Image-based Application for Respirator Sizing), a novel tool which provides respirator size recommendations based on a facial image and basic user demographics. This solution obviates the need for an in-person assessment, providing an accurate size recommendation within seconds. The application has the potential to reduce time-per-worker respirator fitting, reduce overall respirator usage, and increase safety by providing hospitals with a non-contact option for sizing. Furthermore, future applications may assist healthcare institutions optimize supply chains by providing rapid assessments and re-assessments of appropriate respirator sizes used by their workers. Early testing indicated accuracy of 71.3% for the software (N=16), and further testing is underway at Houston Methodist Hospital.
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