电子听诊系统:听诊数据的处理

А. О . Макалов, Владимир Алексеевич Смирнов, А. В. Прохорцов, A. O. Makalov, V. A. Smirnov, A. Prokhortsov
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引用次数: 0

摘要

研究的目的是增加具有测量特性和测试的电子听诊系统设计的多样性。该系列文章包括电子听诊系统模型的开发,电子听诊器的设计,实验样品的制作,测量电子听诊器和经典听诊器的幅频特性的方法的开发,所提出的模型和方法的测试,听诊数据的分析。本文探讨了听诊数据初步分析的数学方法。实验中使用了正常呼吸和呼吸困难的记录。对呼吸音进行频率、时频和自相关分析。方法。该研究以数字信号处理理论为基础。该研究使用了从电子听诊系统的实验样本中获得的听诊数据。采用左中肺硬(病理)呼吸和正常呼吸的电子记录。采用以下参数将呼吸噪声转换为数字形式:采样频率fd = 48 kHz;位深度n = 24位;通道数1。为了分析记录的频率信息含量,构造了它们的频谱。利用快速傅里叶变换计算光谱值。结果。在本工作中,分析了硬呼吸和正常呼吸记录的频率特征。得到了自相关函数的取值。得到了正常呼吸过程的作者回归模型。分析确定模型顺序的问题仍然悬而未决,需要单独解决。当一个均匀的信号被应用到它的输入时,由此产生的模型允许你产生吸入或呼出的等效呼吸噪声。结论。对电子听诊系统进行了测试,提出了简化听诊数据初步分析的方法。由于样本量小,治疗呼吸困难和呼吸正常的结果差异无统计学意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Electronic Auscultation System: Processing of Auscultatory Data
   The purpose of research is to increase the diversity of electronic auscultation system designs with measured characteristics and testing.   The series of articles includes the development of a model of the electronic auscultation system, the design of an electronic stethoscope, the manufacture of an experimental sample, the development of a methodology for measuring the amplitude-frequency characteristics of electronic and classical stethoscopes, testing of the proposed models and methods, analysis of auscultative data. The article considers mathematical methods of primary analysis of auscultative data. Recordings of normal and hard breathing were used for the experiment. Frequency, time-frequency and autocorrelation analysis of respiratory sounds was performed.   Methods. The research was based on the theory of digital signal processing. The study uses auscultative data obtained from an experimental sample of an electronic auscultation system. Electronic records of hard (pathological) and normal human breathing over the left middle lung were used. Respiratory noises were converted into digital form with the following parameters: sampling frequency fd = 48 kHz; bit depth n = 24 bits; number of channels 1. To analyze the frequency information content of the recordings, their spectra were constructed. A fast Fourier transform was used to calculate the values in the spectra.  Results. In the presented work, the frequency characteristics of recordings of hard and normal breathing are analyzed. The values of autocorrelation functions are obtained. An author-regression model of the process of normal breathing is obtained. The problem of analytical determination of the model order remains open and requires a separate solution. The resulting model allows you to generate an equivalent breathing noise of inhalation or exhalation when a signal with a uniform is applied to its input.   Conclusion. A sample of the electronic auscultation system has been tested, methods of simplified primary analysis of auscultative data have been proposed. The difference in the results of the treatment of hard and normal breathing has no statistical significance due to the small sample.
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