Covid Cough Classification using KNN Classification Algorithm

ABSTRACT

Covid 19 is an infectious disease that is caused by infection due to SARS-CoV-2 virus. The vast majority of people infected with Corona virus will encounter mild to moderate symptoms and recover without any special treatment. In some case, some people become seriously ill and require clinical consideration. Because of the increase in number of death due to COVID-19, an techniques for the early discovery of the illness is very much needed that might assist with restricting its spread just as help in the development of targeted surrounding solutions. Coughs and other vocal sounds contain pulmonary health data that can be utilized for symptomatic purposes, and ongoing examinations in chaotic dynamics have shows a nonlinear phenomenon exists in vocal signs. Cough samples are transformed with Mel frequency Cepstral Coefficients (MFCC) and the cough audio data is fitted into a GridsearchCV model with KNN based classification algorithm. The number of training data for used for training our model is 217 and remaining 55 data were used for testing the model. The dataset contains the cough tests from both male and female. When evaluated the model could get a precision of 83.3%. © 2022 IEEE.