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Classification of heart sound based on multipoint auscultation system

机译:基于多点听诊系统的心音分类

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Heart disorder can be diagnosed by listening to the heart sound that is recorded using stethoscope on the human chest. However, human interpretation and diagnosis based on auscultation is somewhat subjective and vary depending on the skill and hearing ability of the physician. Studies have been focusing on the development and evaluation of methods in detecting the various components of the heart sound at a specific auscultation point. The principle interest of this paper is, however focused towards finding the optimal auscultation point which involves placing the stethoscope at different position namely at the aortic valve and pulmonary valve which provide better quality of the second heart sound component (S2) and mitral valve and tricuspid valve where the first heart sound component (Sl) can be heard more clearly. Comparative experiments using to Mel-Frequency Cepstrum Coefficient (MFCC) property, variation of the number of Hidden markov Model (HMM) states and variation of the number of gaussian mixtures were conducted to measure the offects of these factors to the classification performance at the four locations of auscultation point. Further works was also carried out with time-frequency distribution which is known to provide information about how the spectral content of the signal evolves with time. The Extended Modified B-distribution was chosen from a number of time-frequency methods due to its ability to represent the signal in the most efficient way in term of noise and cross term elimination.
机译:可以通过听取用听诊器在人胸上录制的心音来诊断心脏病。然而,基于听诊的人类解释和诊断在某种程度上是主观的,并且取决于医师的技能和听力。研究一直集中于在特定听诊点检测心音的各种成分的方法的开发和评估。然而,本文的主要兴趣集中在寻找最佳听诊点,这涉及将听诊器放置在不同的位置,即位于主动脉瓣和肺动脉瓣处,从而提供更好的第二心音成分(S2)以及二尖瓣和三尖瓣的质量可以更清楚地听到第一心音成分(S1)的瓣膜。利用梅尔倒谱系数(MFCC)特性,隐马尔可夫模型(HMM)状态数量的变化和高斯混合物数量的变化进行了对比实验,以测量这四个因素对分类性能的影响听诊点的位置。还利用时频分布进行了进一步的工作,该时频分布可提供有关信号频谱内容如何随时间演变的信息。扩展修改B分布是从多种时频方法中选择的,因为它具有以噪声和交叉项消除的最有效方式表示信号的能力。

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