Implementation of Paper-based Sensor into Disposible Masks for Continous Respiratory Monitoring for Telemonitoring

COVID-19是一种基于呼吸道的大流行。由于呼吸困难是一个重要的症状，没有定量的方法来监测关键工作人员或最脆弱的个体的早期症状。通过将Spyras技术集成到口罩中，我们旨在监测呼吸模式窘迫，并指出COVID-19可能导致的恶化。预计到2020年，仅在中国，口罩的产量就将达到100亿只（Lai Lin Thomala, 2020），而且使用这些口罩的人接触COVID-19的风险很高，因此，通过嵌入口罩内的呼吸分析来预测可能的传染的方法变得很有吸引力。在抗击病毒的过程中，戴口罩的好处是众所周知的，也是临床实践的一部分，捷克共和国、摩洛哥和纽约等国家正在强制要求公众戴口罩。个人防护装备是一种持续有限的资源。Spyras可以将其高精度的纸质传感器集成到3层和FFP2/3口罩中，通过替换现有的单向阀，将对现有制造实践的干扰降到最低。一个可重复使用的电子设备将包含在一个小模块中，该模块连接到一次性掩模滤波器和传感器。移动应用程序将连接到口罩中的传感器，提供呼吸分析。这款移动应用程序不仅可以收集呼吸数据，还可以作为症状追踪器，在用户输入定性数据时监测咳嗽、呼吸困难和体温。通过远程应用程序收集的数据可以传递到安全的云平台，并为用户提供交互式数据仪表板，以查看他们的口罩佩戴情况，并提供过滤器效率和更换新过滤器的时间等信息，以保持过滤器效率。在Innovate UK的资助下，Spyras将能够重新部署和开发其平台，从监测运动和医院中的个人呼吸，到在工作或户外佩戴口罩，并对他们的个人健康状况采取更慎重的方法。Spyras可以为病毒后支持扩展应用程序功能，例如实施康复指导和措施。这是为了减少限制措施解除后出现“第二波”感染的可能性，并确保个人应对此类全球事件的后果。此外，这将对COVID-19后人群的恢复产生积极影响。从过去的冠状病毒爆发（如SARS和中东呼吸综合征）来看，不仅需要在ICU住院的患者在康复后进行康复（Chan 2005）。在过去3个月的工作中，早期原型从临床通风测试到用户组测试，通过“影响扩展”基金扩大资助将大大建立在这一工作的基础上。这将通过与我们选择的供应商合作来实现，从最初的可行性临床试验到用户试验中可以依赖的设备，生产可扩展的纸质传感器墨盒。具有传感器之间的低可变性和提供这些传感器的专业知识，将为用户测试提供最佳条件。

COVID-19 is a respiratory based pandemic. With breathlessness being a vital symptom, there is no quantitative method for monitoring essential workers or the most vulnerable individuals for early symptoms. Using Spyras technology incorporated into face masks, we aim to monitor breathing pattern distress and indicate possible deterioration from COVID-19.With the predicted production volumes of face masks reaching 10 Billion in 2020 only in China(Lai Lin Thomala, 2020) and the high risk of exposure of the people using these masks to COVID-19 a means to predict possible contagion through respiratory analysis embedded within the mask becomes attractive. The benefits of wearing face mask in the fight against the virus are understood and part of clinical practice to wear, countries like Czech Republic, Morocco, and New York are making masks mandatory for the public.Personal protective equipment is a continuing limited resource. Spyras can integrate its highly accurate paper sensors into 3-ply and FFP2/3 respirator masks with minimal disruption to existing manufacturing practices by replacing the one way valves that exist. A reusable electronics would be contained within a small module that connects to the disposable mask filter and sensor. A mobile application would connect to the sensor in the mask providing respiratory analytics. This mobile app would not only gather respiratory data but also work as a symptoms tracker to monitor coughs, breathlessness and temperature when the user inputs qualitative data. Data collected through a remote app can be passed to a secure cloud platform and provide an interactive data dashboard for users to view their mask wearing and provide information on the filter efficiency and times to change to new filters to maintain filter efficiency.With funding from Innovate UK, Spyras will be able to redeploy and develop its platform from monitoring the breathing of individuals in sports and hospitals, to face masks at work or outside and take a more measured approach in their individual health profiles.Spyras can extend app features for post virus support, such as implementation of rehabilitation instruction and measures. This is to reduce the possibility of a 'second wave' of infection when restrictive measures are lifted and to assure individuals with the aftermath of such a global event. Moreover, this would positively impact the recovery of people post COVID-19. As seen from coronavirus outbreaks of the past such as SARS and MERS there will be a need for rehabilitation post healing not only for patients who have been hospitalised in ICU(Chan 2005).Extending the funding by the 'Extension for Impact' funding will significantly build on the past 3 months of work where early prototypes were placed through clinical ventilation testing to user group testing. This will be achieved by working with our chosen suppliers to produce a scalable paper sensor cartridge from the initial feasibility clinical trial to a device that can be relied upon in user trials. Having low variability between sensors and expertise in place to supply these sensors, will enable to optimal conditions for user testing.