Development of MEMS accelerometer based real time data acquisition prototype for COVID-19 patient breath monitoring and assessment

Abstract

In late 2019, coronavirus-2, a dangerous human pathogen that causes the disease coronavirus disease 2019, arose as a severe human pathogen (COVID-19). Acute respiratory failure, which is similar to acute respiratory distress syndrome, is the most frequent clinical presentation of extreme COVID-19. COVID-19 includes diseases of the airway, lung parenchymal, pulmonary vascular, and respiratory neuromuscular systems. This essay summarises what is learned about the impact of coronavirus-2 infection on various areas of the respiratory system, provides insights into the basic pathology of respiratory disease, and highlights current and prospective translational and clinical research. This paper discusses economic and reliable respiratory monitoring systems using prototype popular embedded controller and built-in smartphone MEMS accelerometer. The hardware is tested and implemented on healthy, and Covid-19 affected persons for respiratory data, and Correlation has been made among them. One class SVM(Support Vector Machine) learning algorithm further processes the data collected from the sensor. The project primarily aims to detect anomalies in the respiratory data set to assess the rate of respiration by matching the data sets of a healthy individual and a COVID infected person.