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Wi-COVID: A COVID-19 symptom detection and patient monitoring framework using WiFi. | LitMetric

AI Article Synopsis

  • COVID-19 is a severe pandemic causing rapid pulmonary deterioration and high mortality, straining global healthcare resources
  • Non-critical patients are often sent home for self-isolation, which necessitates new ways to monitor their health remotely
  • This paper introduces Wi-COVID, a non-invasive technology that uses WiFi signals to track respiration rates of COVID-19 patients at home, presenting a framework for remote monitoring along with preliminary results.

Article Abstract

The current SARS-CoV-2, better know as COVID-19, has emerged as a serious pandemic with life-threatening clinical manifestations and a high mortality rate. One of the major complications of this disease is the rapid and dangerous pulmonary deterioration that can lead to critical pneumonia conditions, resulting in death. The current healthcare system around the world faces the potential problem of lacking resources to assist a large number of patients at the same time; then, the non-critical patients are mostly referred to perform self-isolation/quarantine at home. This pandemic has placed new demands on the , asking for novel, rapid and secure ways to monitor patients in order to detect and quickly report patient's symptoms to the healthcare provider, even if they are not in the hospital. While tremendous efforts have been done to develop technologies to detect the virus, create the vaccine, and stop the spread of the disease, it is also important to develop IoT technologies that can help track and monitor diagnosed COVID-19 patients from their homes. In this paper, we explore the possibility of monitoring respiration rates (RR) of COVID-19 patients using a widely-available technology at home - WiFi. Using the at-home WiFi signals, we propose Wi-COVID, a non-invasive and non-wearable technology to monitor the patient and track RR for the healthcare provider. We first introduce the currently available applications that can be done using WiFi signals. Then, we propose the framework scheme for an end-to-end non-invasive monitoring platform of the COVID-19 patients using WiFi. Finally, we present some preliminary results of the proposed framework. We envision the proposed platform as a life-changing technology that leverages WiFi technology as a non-wearable and non-invasive way to monitor COVID-19 patients at home.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680085PMC
http://dx.doi.org/10.1016/j.smhl.2020.100147DOI Listing

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