Discrimination of Patients with Chronic Obstructive Pulmonary Disease and Bronchial Asthma by Applying Machine Learning Methods to analyze Electronic Gas-Sensing Data

• Main Authors: Li,You Jin, 李宥瑾
• Other Authors: Liu, Yi-Wen
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/51351056488919289041

碩士 === 國立清華大學 === 電機工程學系 === 103 === The use of artificial olfactory technology to assist medical diagnosis is a promising domain for electronic applications. Since bronchial asthma (BA) and chronic obstructive pulmonary disease (COPD) have very similar symptoms, being able to detect and discriminate them automatically would have positive impact in the clinics. In this research, we focused on this topic and used a chemical sensing array to detect the gas exhaled from the patients. Signal preprocessing techniques were applied to remove the baseline drift and normalize the influence of concentration between samples. Then, methods for gas classification involved the following steps: first, we determined whether the gas was produced by a patient who suffered from either kind of the diseases. Secondly, if the classification result was positive, we applied further analysis to tell what kind of disease the patient had. Finally, we analyzed the severity of the patients. The method of classification was based on principal component analysis (PCA) and linear discriminant analysis to reduce the dimension of data. After that, we compared the result of the support vector machine and the K nearest neighbor method to achieve the best performance. We used the receiver operating curve and the area under the curve to assess the reliability and validity of the classifier. In addition, we observed the weights of the sensors in reduced dimensions of PCA and checked whether the main components of the analyzed result agreed with the list of commonly observed volatile organic compounds in the gas exhaled by patients of COPD and BA. The results of the identification all have a recognition rate of above 80%. Also, PCA-based analyses indicate that xylene, which is one of the volatile organic compounds found in gas exhaled by COPD patients, is a key compound that enable discrimination of COPD and BA.