A Non-Linear Feature Extraction Method of Physiological Signals Based on Empty Arrangement

Abstract

The invention discloses a method for extracting nonlinear features of physiological signals based on empty arrays, which is applied in the field of physiological signal processing. Aiming at the lack of parameter extraction and analysis of nonlinear features of physiological signals based on empty arrays in the prior art, the present invention uses The acquired physiological signal is symbolized by equivalent arrangement to obtain a first vector and its first arrangement type; then find a symmetrical arrangement type of the first arrangement type, and classify the first arrangement type and its symmetrical arrangement type into a first combination; Then find the symmetric vector of the first vector, and obtain the permutation type of the symmetric vector, record it as the second permutation type, classify the first permutation type and the second permutation type into the second combination; then according to the first combination and the second Combining to build a joint permutation group, and counting the feature quantities in the joint permutation group; finally extracting the nonlinear characteristic parameters of the physiological signal according to the feature quantity; the method of the present invention can correctly and effectively characterize the physiological signals under different physiological states based on the empty permutation.

Description

technical field [0001] The invention belongs to the field of physiological signal processing, in particular to a symbolic time series analysis of physiological signals and a nonlinear analysis technique of statistical physics. Background technique [0002] The physiological regulation system of the human body is a nonlinear complex system. Most of the existing nonlinear analysis methods need to calculate the probability distribution, which is not easy for the physiological time series with unknown characteristics. A current effective solution is symbolic time series analysis, that is, converting the original sequence into a sequence containing only individual values. This method can extract the symbolic dynamics characteristics of the sequence while simplifying probability estimation, and is simple, fast, and resistant noise characteristics. Among the symbolic methods, the permutation method fully characterizes the structural characteristics of the sequence by using the siz...

AI Technical Summary

Problems solved by technology

Some studies have shown that the characteristics of the distribution of empty arrays (including such characteristics as pseudo-null arrays, empty array reduction ratios, and lack of symmetrical arrays) contain certain characteristics of physiological dynamic systems. However, how to extract them from the distribution of empty arrays? The nonlinear characteristics of complex physiological systems have not been effectively resolved

At present, there are not many parameters that directly use empty arrays to extract system features, and it is not easy to extract nonlinear features in physiological signals simply from the perspective of empty array distribution. The method of using empty arrays often needs to be combined with corresponding statistical concepts for comprehensive analysis. Therefore, It is difficult to extract the nonlinear characteristics of physiological signals of different physiological and case states according to the distribution of empty arrays

[0004] In short, the system information contained in the empty array is beneficial to the nonlinear analysis of the physiological system, but the relationship between the array types is more complicated, so how to use the parameters based on the empty array to extract and analyze the nonlinear characteristics of the physiological signal is a meaningful and at the same time. complicated question

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