Contemporary Model to Predict Clinical Emergency Treatment Categorization in Covid-19 Positive using Cough Audio Signal and Multi Class SVM

  • Jyothi N. M., V. Murali Mohan, S. Madhusudanan

Abstract

Coivd-19 pandemic has paralyzed the medical system throughout the world. With almost majority of the population affected by the disease, there is critical  need to handle the systematic treatment of the patients which helps the medical system /government to plan and manage the allocation of medical  resources like health workers ,beds, medicines, vaccination and very importantly  oxygen cylinders. This research is done to  predict the classification of Covid-19 infected patients   based on the smart phone recorded cough audio signal obtained by them. After through pre-processing of the cough sound, cough features are extracted and multi class SVM learning model is applied for the prediction of Emergency Treatment Level classification as Low, Medium and High and experiment is successful in predicting the classification with overall 96% accuracy and precision.

Published
2021-11-11
How to Cite
Jyothi N. M., V. Murali Mohan, S. Madhusudanan. (2021). Contemporary Model to Predict Clinical Emergency Treatment Categorization in Covid-19 Positive using Cough Audio Signal and Multi Class SVM. Design Engineering, 11374 - 11386. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/6210
Section
Articles