Wavelet introscopy of human organism bionets

G. Aldonin, V. V. Cherepanov
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Abstract

In domestic and foreign practice, a great deal of experience has been accumulated in the creation of means for monitoring the functional state of the human body. The existing complexes mainly analyze the electrocardiogram, blood pressure and a number of other physiological parameters. Diagnostics is often based on formal statistical data which are not always correct due to the nonstationarity of bioprocesses and without taking into account their physical nature. An urgent task of monitoring the state of the cardiovascular system is the creation of effective algorithms for computer technologies to process biosignals based on nonlinear dynamic models of body systems since biosystems and bioprocesses have a nonlinear nature and fractal structure. The nervous and muscular systems of the heart, the vascular and bronchial systems of the human body are examples of such structures. The connection of body systems with their organization in the form of self-similar fractal structures with scaling close to the “golden ratio” makes it possible to diagnose them topically. It is possible to obtain detailed information about the state of the human body’s bio-networks for topical diagnostics on the basis of the wavelet analysis of biosignals (the so-called wavelet-introscopy). With the help of wavelet transform, it is possible to reveal the structure of biosystems and bioprocesses, as a picture of the lines of local extrema of wavelet diagrams of biosignals. Mathematical models and software for wavelet introscopy make it possible to extract additional information from biosignals about the state of biosystems. Early detection of latent forms of diseases using wavelet introscopy can shorten the cure time and reduce the consequences of disorders of the functional state of the body (FSO), and reduce the risk of disability. Taking into account the factors of organizing the body’s biosystems in the form of self-similar fractal structures with a scaling close to the “golden ratio” makes it possible to create a technique for topical diagnostics of the most important biosystems of the human body.
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人体生物网的小波内窥镜
在国内外的实践中,在创造人体功能状态监测手段方面积累了大量的经验。现有的复合体主要分析心电图、血压和其他一些生理参数。诊断通常基于正式的统计数据,由于生物过程的非平稳性和没有考虑其物理性质,这些数据并不总是正确的。由于生物系统和生物过程具有非线性性质和分形结构,因此监测心血管系统状态的一项紧迫任务是创建有效的计算机技术算法来处理基于身体系统非线性动态模型的生物信号。心脏的神经和肌肉系统,人体的血管和支气管系统都是这种结构的例子。人体系统与其组织以自相似分形结构的形式联系在一起,其尺度接近“黄金比例”,这使得局部诊断成为可能。在生物信号的小波分析(所谓的小波内窥镜)的基础上,可以获得关于人体生物网络状态的详细信息,用于局部诊断。小波变换可以作为生物信号小波图的局部极值线的图像来揭示生物系统和生物过程的结构。小波内窥镜的数学模型和软件使从生物信号中提取有关生物系统状态的附加信息成为可能。利用小波内窥镜对疾病的潜伏形式进行早期检测,可以缩短治疗时间,减少机体功能状态(FSO)紊乱的后果,降低致残的风险。考虑到以自相似分形结构的形式组织人体生物系统的因素,其尺度接近“黄金比例”,这使得创造一种对人体最重要的生物系统进行局部诊断的技术成为可能。
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