Detection of patients considering observation frequency of continuous and discontinuous adventitious sounds in lung sounds.

We propose an improved approach for distinguishing between healthy subjects and patients with pulmonary emphysema by the use of one stochastic acoustic model for continuous adventitious sounds and another for discontinuous adventitious sounds. These models are able to represent the spectral features of the adventitious sounds for the detection of abnormal respiration. However, abnormal respiratory sounds with unclassifiable spectral features are present among the continuous and discontinuous adventitious sounds and mixing noises. These sounds cause difficulties in achieving a highly accurate classification. In this study, the difference in occurrence frequencies between two types of adventitious sounds for each considered auscultation point and inspiration/expiration was considered. This difference, in combination with the confusion tendency of the classifier, was formulated as the validity score of each respiratory sound. The conventional spectral likelihood and the newly formulated validity score were combined to perform detection of abnormal respiration and patients. In the classification of healthy subjects and patients, the proposed approach achieved a higher classification rate (87.7%) than the conventional method (85.2%), demonstrating the statistical superiority (5% level) of the former.