Literature DB >> 17010961

Nonlinear analysis of wheezes using wavelet bicoherence.

Styliani A Taplidou1, Leontios J Hadjileontiadis.   

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.

Entities:  

Mesh:

Year:  2006        PMID: 17010961     DOI: 10.1016/j.compbiomed.2006.08.007

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  3 in total

1.  Tracking and time-frequency analysis on nonlinearity of tracheal sounds.

Authors:  F Jin; F Sattar
Journal:  Med Biol Eng Comput       Date:  2009-02-18       Impact factor: 2.602

2.  An acoustical respiratory phase segmentation algorithm using genetic approach.

Authors:  F Jin; F Sattar; D Y T Goh
Journal:  Med Biol Eng Comput       Date:  2009-07-29       Impact factor: 2.602

3.  A wavelet bicoherence-based quadratic nonlinearity feature for translational axis condition monitoring.

Authors:  Yong Li; Xiufeng Wang; Jing Lin; Shengyu Shi
Journal:  Sensors (Basel)       Date:  2014-01-27       Impact factor: 3.576

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.