title: Lung sound analysis for wheeze episode detection.
abstract: Listening and interpreting lung sounds by a stethoscope had been an important component of screening and diagnosing lung diseases. However this practice has always been vulnerable to poor audibility, inter-observer variations (between different physicians) and poor reproducibility. Thus computerized analysis of lung sounds for objective diagnosis of lung diseases is seen as a probable aid. In this paper we aim at automatic analysis of lung sounds for wheeze episode detection and quantification. The proposed algorithm integrates and analyses the set of parameters based on ATS (American Thoracic Society) definition of wheezes. It is very robust, computationally simple and yielded sensitivity of 84% and specificity of 86%.
authors.affiliation: Philips Research Asia-Bangalore, Bangalore, India. Abhishekdr.jain@philips.com
authors.forename: Abhishek
authors.initials: A
authors.lastname: Jain
authors.forename: Jithendra
authors.initials: J
authors.lastname: Vepa
mesh_terms: D000465:Algorithms; D001249:Asthma / Q000150:complications / Q000175:diagnosis* / Q000503:physiopathology; D003936:Diagnosis, Computer-Assisted; D004867:Equipment Design; D006801:Humans; D008168:Lung / Q000473:pathology; D008171:Lung Diseases / Q000175:diagnosis / Q000473:pathology; D012129:Respiratory Function Tests / Q000295:instrumentation / Q000379:methods; D012135:Respiratory Sounds / Q000175:diagnosis* / Q000209:etiology; D012680:Sensitivity and Specificity; D012984:Software; D013997:Time Factors