Wheeze detection based on time-frequency analysis of breath sounds

Authors:
Styliani A. Taplidou;Leontios J. Hadjileontiadis
Affiliations:
Faculty of Engineering, Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, University Campus, GR 541 24 Thessaloniki, Greece;Faculty of Engineering, Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, University Campus, GR 541 24 Thessaloniki, Greece
Venue:
Computers in Biology and Medicine
Year:
2007

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Abstract

Abnormal breath sounds like wheezes are observed in patients with obstructive pulmonary diseases. The aim of this study was to construct an automatic technique for wheeze detection and monitoring using spectral analysis. Wheezes from 13 patients with diagnosed asthma, chronic obstructive pulmonary disease and pneumonia were recorded and a time-frequency wheeze detector (TF-WD) based on TF wheeze characteristics was constructed. The TF-WD was evaluated using 337 wheezes by comparing its findings with those from clinical auscultation performed by two experts. In addition, the TF-WD was tested against artificial noise. The experimental and testing results justified the efficient performance and high noise robustness of the TF-WD.