A Review on Detection of Covid Symptoms

Telemedicine may hold the key to limiting the emerging coronavirus disease's global outbreak (COVID-19). The COVID-19 virus directly affects the lungs, causing pneumonia-like symptoms and shortness of breath, both of which can be fatal. Despite the fact that self-quarantine and social isolation are crucial during a pandemic, the technique for identifying COVID-19 contraction via nose swabs, saliva test kits, and blood testing is routinely available at healthcare facilities. As a result, developing customized self-testing kits for the COVID-19 virus and related viruses is a top goal. Many e-health initiatives are now possible thanks to smartphones with embedded software, hardware, high-performance computation, and networking capabilities. COVID-19 contracted users' breathing sounds may reveal certain acoustic signal patterns that are worth researching, according to a thorough assessment of breathing sounds and their implications in recognizing respiratory issues. Obtaining respiratory data solely from breathing noises input into a smartphone's microphone appears to be an intriguing solution in this area. Advanced signal processing and analysis, in conjunction with modern deep/ machine learning and pattern recognition algorithms, can be used to analyze the obtained breathing sounds to separate the breathing phases, estimate lung volume, oxygenation, and further classify the breathing data input into healthy or unhealthy situations. For the ongoing global COVID-19 pandemic, the concepts mentioned have the potential to be employed as self-test breathing monitoring apps, with users being able to check their breathing sound pattern on a frequent basis.