title: Automatic Wheezing Detection Based on Signal Processing of Spectrogram and Back-Propagation Neural Network.
abstract: Wheezing is a common clinical symptom in patients with obstructive pulmonary diseases such as asthma. Automatic wheezing detection offers an objective and accurate means for identifying wheezing lung sounds, helping physicians in the diagnosis, long-term auscultation, and analysis of a patient with obstructive pulmonary disease. This paper describes the design of a fast and high-performance wheeze recognition system. A wheezing detection algorithm based on the order truncate average method and a back-propagation neural network (BPNN) is proposed. Some features are extracted from processed spectra to train a BPNN, and subsequently, test samples are analyzed by the trained BPNN to determine whether they are wheezing sounds. The respiratory sounds of 58 volunteers (32 asthmatic and 26 healthy adults) were recorded for training and testing. Experimental results of a qualitative analysis of wheeze recognition showed a high sensitivity of 0.946 and a high specificity of 1.0.
authors.affiliation: Department of Computer Science and Information Engineering, National Taipei University, New Taipei City, Taiwan.
authors.forename: Bor-Shing
authors.initials: BS
authors.lastname: Lin
authors.affiliation: Department of Integrated Diagnostics and Therapeutics, National Taiwan University Hospital, Taipei, Taiwan.
authors.forename: Huey-Dong
authors.initials: HD
authors.lastname: Wu
authors.affiliation: Department and Graduate Institute of Electrical Engineering, National Taiwan University, Taipei, Taiwan.
authors.forename: Sao-Jie
authors.initials: SJ
authors.lastname: Chen
mesh_terms: D000328:Adult; D000465:Algorithms; D001249:Asthma / Q000503:physiopathology; D016022:Case-Control Studies; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D008875:Middle Aged; D016571:Neural Networks, Computer; D012135:Respiratory Sounds / Q000145:classification* / Q000175:diagnosis*; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography / Q000145:classification / Q000379:methods*