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Lung Consolidation Detection through Analysis of Vocal Resonance Signals

机译:通过声共振信号分析检测肺合并

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Consolidation of the lung is a common pathology which is sometimes life threatening. One of the primary causes is the infection of lung tissue (pneumonia). Vocal resonance and vocal fremitus are part of the routine clinical examination of the respiratory system by physicians, which although time consuming, helps in the diagnosis of consolidation of the lung. In this paper, we suggest a possible automatic lung consolidation detection system that can be used by health workers with basic training. Analysis is performed on the vocal resonance sound signals recorded using an electronic stethoscope from the chest walls of normal subjects and patients. We show that for the detection system, use of signal loudness, which is generally considered by physicians, would be infeasible and propose that signal power spectral density computed using our system be considered. Certain frequency regions in the power spectral density (periodogram) are proved to be significant indicators of lung consolidation using t-tests. These findings are then applied to design the detection system using Gaussian naive Bayes classifiers.
机译:肺部巩固是一种常见的病理,有时会危及生命。主要原因之一是肺组织感染(肺炎)。声带共鸣和声带颤抖是医生对呼吸系统进行常规临床检查的一部分,尽管这很耗时,但有助于诊断肺结实。在本文中,我们建议一种可能的自动肺巩固检查系统,供基础培训的卫生工作者使用。对使用电子听诊器记录的正常受试者和患者胸壁的声音共振声音信号进行分析。我们表明,对于检测系统而言,使用医师通常认为的信号响度是不可行的,并建议考虑使用我们的系统计算出的信号功率频谱密度。使用t检验证明,功率谱密度(周期图)中的某些频率区域是肺巩固的重要指标。然后将这些发现应用于使用高斯朴素贝叶斯分类器设计检测系统。

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