One of the most significant threats associated with COVID-19 is the increase in hospitaladmission. The primary study gathering the data was integral as the basis of this thesis.The study investigates whether using biosensors to monitor patients infected by COVID-19will impact outcomes compared to patients who are not monitored electronically. Thebiosensors are used to monitor vitals such as heart rate, respiration rate, heart ratevariability, and relative stroke volume of a patient group at home.
An interactive and user-friendly GUI was developed to visualize data from patients thatparticipate in the study. The user can navigate the plot and change settings from a menubar. A vital functionality implemented is the ’Extract data’ function. By extracting data,health care professionals can use the data for further data analysis. Data analysis wasperformed to test the ’Extract Data’ functionality. The analysis compared the respirationrate of two patients by calculating the average, median, and standard deviation. Theresults show that patient 1 has a higher average and median, while patient 2 has a higherstandard deviation.
The GUI is implemented using Python and Qt as a framework; this has been used becauseit is open-source and easy to install or import. Python is an object-oriented languagewith clear syntax.