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基于声学的使用高斯混合模型分类法对呼吸道疾病的评估

Acoustics based assessment of respiratory diseases using GMM classification.

作者信息

Mayorga P, Druzgalski C, Morelos R L, Gonzalez O H, Vidales J

机构信息

Instituto Tecnológico de Mexicali, B.C., México.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:6312-6. doi: 10.1109/IEMBS.2010.5628092.

Abstract

The focus of this paper is to present a method utilizing lung sounds for a quantitative assessment of patient health as it relates to respiratory disorders. In order to accomplish this, applicable traditional techniques within the speech processing domain were utilized to evaluate lung sounds obtained with a digital stethoscope. Traditional methods utilized in the evaluation of asthma involve auscultation and spirometry, but utilization of more sensitive electronic stethoscopes, which are currently available, and application of quantitative signal analysis methods offer opportunities of improved diagnosis. In particular we propose an acoustic evaluation methodology based on the Gaussian Mixed Models (GMM) which should assist in broader analysis, identification, and diagnosis of asthma based on the frequency domain analysis of wheezing and crackles.

摘要

本文的重点是提出一种利用肺音对与呼吸障碍相关的患者健康状况进行定量评估的方法。为了实现这一目标,我们利用了语音处理领域内适用的传统技术来评估通过数字听诊器获得的肺音。评估哮喘的传统方法包括听诊和肺活量测定,但使用目前可用的更灵敏的电子听诊器以及应用定量信号分析方法提供了改进诊断的机会。特别是,我们提出了一种基于高斯混合模型(GMM)的声学评估方法,该方法应有助于基于哮鸣音和湿啰音的频域分析对哮喘进行更广泛的分析、识别和诊断。

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