title: Nonlinear analysis of wheezes using wavelet bicoherence.
abstract: Wheezes, as being abnormal breath sounds, are observed in patients with obstructive pulmonary diseases, such as asthma. The aim of this study was to capture and analyze the nonlinear characteristics of asthmatic wheezes, reflected in the quadrature phase coupling of their harmonics, as they evolve over time within the breathing cycle. To achieve this, the continuous wavelet transform (CWT) was combined with third-order statistics/spectra. Wheezes from patients with diagnosed asthma were drawn from a lung sound database and analyzed in the time-bi-frequency domain. The analysis results justified the efficient performance of this combinatory approach to reveal and quantify the evolution of the nonlinearities of wheezes with time.
authors.affiliation: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR 541 24 Thessaloniki, Greece. stellata@auth.gr
authors.forename: Styliani A
authors.initials: SA
authors.lastname: Taplidou
authors.forename: Leontios J
authors.initials: LJ
authors.lastname: Hadjileontiadis
mesh_terms: D000465:Algorithms; D001249:Asthma / Q000175:diagnosis* / Q000503:physiopathology; D003936:Diagnosis, Computer-Assisted; D005583:Fourier Analysis; D006801:Humans; D008432:Mathematical Computing; D017711:Nonlinear Dynamics; D011381:Programming Languages; D012135:Respiratory Sounds / Q000175:diagnosis* / Q000503:physiopathology; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography