Abstract
In recent years, electronic nose (e-nose) systems have become a focus method for diagnosing pulmonary diseases such as lung cancer. However, principles and patterns of sensor responses in traditional e-nose systems are relatively homogeneous. Less study has been focused on type-different sensor arrays. In this paper, we designed a miniature e-nose system using 14 gas sensors of four types and its subsequent analysis of 52 breath samples. To investigate the performance of this system in identifying and distinguishing lung cancer from other respiratory diseases and healthy controls, five feature extraction algorithms and two classifiers were adopted. Lastly, the influence of type-different sensors on the identification ability of e-nose systems was analyzed. Results indicate that when using the LDA fuzzy 5-NN classification method, the sensitivity, specificity and accuracy of discriminating lung cancer patients from healthy controls with e-nose systems are 91.58%, 91.72% and 91.59%, respectively. Our findings also suggest that type-different sensors could significantly increase the diagnostic accuracy of e-nose systems. These results showed e-nose system proposed in this study was potentially practicable in lung cancer screening with a favorable performance. In addition, it is important for type-different sensors to be considered when developing e-nose systems.
Highlights
In recent years, breath analysis has become a research focus in the field of respiratory disease diagnosis due to its noninvasiveness, convenience and real-time analysis[1]
Simulations revealed the accuracy for lung cancer detection to be over 86%, and subsequent experiments proved that this e-nose system could identify many types of cancers[20, 43]; Blatt et al used metal oxide semiconductor sensor arrays for lung cancer diagnosis with accuracy, sensitivity and specificity all of over 90%44
According to the major components and their concentration ranges in human breath especially from lung cancer patients (Table 1), we selected 14 gas sensors which could be classified into 4 types: metal oxide semiconductor (MOS), hot wire gas, catalytic combustion gas, and electrochemical gas sensors
Summary
Breath analysis has become a research focus in the field of respiratory disease diagnosis due to its noninvasiveness, convenience and real-time analysis[1]. Simulations revealed the accuracy for lung cancer detection to be over 86%, and subsequent experiments proved that this e-nose system could identify many types of cancers[20, 43]; Blatt et al used metal oxide semiconductor sensor arrays for lung cancer diagnosis with accuracy, sensitivity and specificity all of over 90%44. These electronic noses are often based on sensor arrays with similar response principles. Hydrogen sulfide Decane, 4-methyoctane, undecane, aldehydes, benzene and its derivatives, 1-butanol Methyl-mercaptan Naphthalene, 1-methyl- and cyclohexane, 1,4-dimethyl-
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