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使用小波双相干性对哮鸣声进行非线性分析。

Nonlinear analysis of wheezes using wavelet bicoherence.

作者信息

Taplidou Styliani A, Hadjileontiadis Leontios J

机构信息

Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR 541 24 Thessaloniki, Greece.

出版信息

Comput Biol Med. 2007 Apr;37(4):563-70. doi: 10.1016/j.compbiomed.2006.08.007. Epub 2006 Sep 29.

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.

摘要

哮鸣音作为异常呼吸音,在患有阻塞性肺部疾病(如哮喘)的患者中可以观察到。本研究的目的是捕捉和分析哮喘哮鸣音的非线性特征,这些特征反映在其谐波的正交相位耦合中,因为它们在呼吸周期内随时间演变。为实现这一目标,将连续小波变换(CWT)与三阶统计量/谱相结合。从肺部声音数据库中提取确诊哮喘患者的哮鸣音,并在时间-双频域中进行分析。分析结果证明了这种组合方法在揭示和量化哮鸣音非线性随时间演变方面的有效性能。

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