Detection of Asthma and Chronic Obstructive Pulmonary Disease (COPD) With an Electronic Nose (E-Nose) Instrumentation System

Abstract

An Electronic Nose (E-Nose) device has been designed to detect asthma and Chronic Obstructive Pulmonary Disease (COPD) through breathing air. This tool consists of hardware and software. E-Nose It consists of a gas sensor that can respond quickly to the elements volatile organic compound (VOC) contained in the respiratory air. The method used is the method Principal Component Analysis (PCA) and Artificial Neural Network (ANN) algorithms backpropagation which is the most precise method of visually classifying types of disease. From the test results using the PCA and ANN methods, it is found that E-Nose can distinguish COPD and asthma with a correlation accuracy of 99.5% percentage and degree Mean Squared Error (MSE) of 0.005.