Abstract
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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More From: Proceedings of the Southwest State University. Series: IT Management, Computer Science, Computer Engineering. Medical Equipment Engineering
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