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Lung sound analysis based methodology to identify asthmatic patient for low power low cost embedded system

机译:基于肺部声音分析方法识别低功耗低成本嵌入式系统的哮喘患者

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In this paper, lung sounds of healthy normal, asthmatic patients, tuberculosis patients, rheumatoid patients and pneumonia patients are analyzed and classified to diagnose asthmatic patients for designing and development of low power, low cost portable embedded system. These lung sounds are analyzed using wavelet packet transform (WPT) to get different sub-band coefficients. From the sub- bands coefficients of different lung sound signal statistical features vectors are extracted. New LVQ (ANN) is used to categorize lung sound signals as asthmatic or non asthmatic. Data is obtained in normal hospital conditions by a typical stethoscope. Total 26 patient and 10 healthy person databases are tested. The proposed Methodology provides 86.6% of accuracy.
机译:本文分析了肺部健康正常,哮喘患者,结核病患者,类风湿性患者和肺炎患者,分类为诊断哮喘患者的设计和开发低功耗,低成本便携式嵌入式系统。使用小波包变换(WPT)分析这些肺部声音以获得不同的子带系数。从不同肺部声音信号统计特征的子带系数提取。新的LVQ(ANN)用于将肺部声音信号分类为哮喘或非哮喘。数据通过典型的听诊器在正常的医院条件下获得。测试了26例患者和10名健康人物数据库。所提出的方法提供了86.6%的准确性。

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