I-Corps: Remote COVID-19 Diagnosis Using a Smart Device

该I-Corps项目的更广泛影响/商业潜力在于开发使用智能设备的远程COVID-19诊断技术。目前的检测方法是面对面的，昂贵，耗时，而且由于高传播风险，对医疗保健提供者和患者来说是不安全的。此外，获得测试结果是耗时的，通常需要等待几天才能得到结果。所提出的技术为COVID-19提供了一种远程、安全、即时、可靠、便携和具有成本效益的诊断测试，可以很容易地与医疗保健提供者共享。这项技术可能会通过远程医疗扩展到疾病检测和健康管理。这个I-Corps项目是基于开发COVID-19诊断解决方案，可以远程检测COVID-19症状。这项创新利用传感器技术和生物医学工程技术，使用智能设备获取受试者与COVID-19症状相关的生理数据。 该技术使用信号处理、图像处理和机器学习算法，从智能设备中的传感器获取的受试者生理数据中检测COVID-19症状。此外，该技术还包括从那些检测结果为阳性和阴性的人中形成一个数据库，以提高COVID-19症状检测的准确性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is in the development of a remote COVID-19 diagnosis technology using a smart device. Current testing methods are face-to-face, expensive, time-consuming, and unsafe for healthcare providers and patients due to high transmission risk. In addition, getting test results is time-consuming and often requires a wait time of several days to get the result. The proposed technology provides a remote, safe, instant, reliable, portable, and cost-effective diagnostic test for COVID-19 that may be readily shared with healthcare providers. This technology may be extended to disease detection and health management via telemedicine.This I-Corps project is based on the development of the COVID-19 diagnosis solution that may remotely detect COVID-19 symptoms. This innovation uses sensor technology and biomedical engineering technology to acquire a subject’s physiology data pertinent to COVID-19 symptoms using a smart device. The technology uses signal processing, image processing, and machine learning algorithms to detect COVID-19 symptoms from the subject’s physiological data acquired by the sensors in the smart device. In addition, the technology includes forming a database from those who test both positive and negative to increase the accuracy of COVID-19 symptom detection.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.