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Pathology information extraction method based on dynamic pulse wave feature parameters

A technology of information extraction and feature parameters, which is applied in the field of integration of information science and medicine, and can solve the problem of low accuracy of dynamic pulse wave feature point extraction.

Inactive Publication Date: 2014-11-05
KUNMING UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is: the present invention provides a method for extracting pathological information based on dynamic pulse wave characteristic parameters. By limiting the start and end positions of each Gaussian wave, it is proposed to use n Gaussian functions to extract pulse wave The method of feature points is used to solve the problem that the extraction accuracy of dynamic pulse wave feature points is not high

Method used

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  • Pathology information extraction method based on dynamic pulse wave feature parameters
  • Pathology information extraction method based on dynamic pulse wave feature parameters
  • Pathology information extraction method based on dynamic pulse wave feature parameters

Examples

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Embodiment 1

[0035] Embodiment 1: as Figure 1-3 As shown, a pathological information extraction method based on dynamic pulse wave characteristic parameters, first find the starting and ending points of the pulse wave; find the confidence interval of the starting and ending points of the pulse wave; judge whether the pulse wave is a normal pulse wave according to the confidence interval of the starting and ending points, Thereby select the normal pulse wave; Calculate the number of Gaussian functions used to fit the i-th normal cycle segment pulse wave again; find out the parameter a of the Gaussian function to the i-th normal cycle segment pulse wave fit k 、c k ; Then find the parameter b k And the Gaussian function expression of the i-th normal cycle segment pulse wave; then find out the 6 feature points of the i-th normal cycle segment pulse wave; then find out the 6 feature points of each normal cycle segment pulse wave in turn, and then Calculate the average value of the characteri...

Embodiment

[0059] Embodiment 2: as Figure 1-3 As shown, a pathological information extraction method based on dynamic pulse wave characteristic parameters, first find the starting and ending points of the pulse wave; find the confidence interval of the starting and ending points of the pulse wave; judge whether the pulse wave is a normal pulse wave according to the confidence interval of the starting and ending points, Thereby select the normal pulse wave; Calculate the number of Gaussian functions used to fit the i-th normal cycle segment pulse wave again; find out the parameter a of the Gaussian function to the i-th normal cycle segment pulse wave fit k 、c k ; Then find the parameter b k And the Gaussian function expression of the i-th normal cycle segment pulse wave; then find out the 6 feature points of the i-th normal cycle segment pulse wave; then find out the 6 feature points of each normal cycle segment pulse wave in turn, and then Calculate the average value of the characteri...

Embodiment 3

[0070] Embodiment 3: as Figure 1-3 As shown, a pathological information extraction method based on dynamic pulse wave characteristic parameters, first find the starting and ending points of the pulse wave; find the confidence interval of the starting and ending points of the pulse wave; judge whether the pulse wave is a normal pulse wave according to the confidence interval of the starting and ending points, Thereby select the normal pulse wave; Calculate the number of Gaussian functions used to fit the i-th normal cycle segment pulse wave again; find out the parameter a of the Gaussian function to the i-th normal cycle segment pulse wave fit k 、c k ; Then find the parameter b k And the Gaussian function expression of the i-th normal cycle segment pulse wave; then find out the 6 feature points of the i-th normal cycle segment pulse wave; then find out the 6 feature points of each normal cycle segment pulse wave in turn, and then Calculate the average value of the characteri...

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Abstract

The invention relates to a pathology information extraction method based on dynamic pulse wave feature parameters and belongs to the technical field of fusion of information science and medical science. The pathology information extraction method comprises the following steps: first searching for starting points and finishing points of pulse waves; solving confidence intervals of the starting points and the finishing points of the pulse waves; judging whether the pulse waves are normal according to the confidence intervals of the starting points and the finishing points so as to select a normal pulse wave; working out the number of gaussian functions for fitting the pulse waves in the I normal period section; solving parameters ak and ck of gaussian functions for fitting the pulse waves in the i normal period section; then solving a parameter bk and a gaussian function expression of the pulse waves in the i normal period section; solving six feature points of the pulse waves in the i normal period section; sequentially solving six feature points of the pulse waves in each normal period section, and solving an average value of the feature points of the pulse waves in all the normal period sections, wherein the average value serves as case information to be analyzed. By means of the pathology information extraction method based on dynamic pulse wave feature parameters, fitting precision is higher, and the feature points of the pulse waves are extracted more accurately.

Description

technical field [0001] The invention relates to a method for extracting pathological information based on dynamic pulse wave characteristic parameters, and belongs to the technical field of fusion of information science and medicine. Background technique [0002] The analysis and extraction method based on dynamic pulse wave characteristic parameters has a very wide range of applications. The application of this method in real-time pulse wave monitoring can not only be used for monitoring diseases in daily life, and users can have a more detailed and accurate understanding of their own physical conditions, but can also be used clinically. Treatment is more important. [0003] At present, there are many research methods on pulse wave feature points. Zhang Junli, Lin Changyan, etc. proposed the correlation relationship between pulse wave waveform period area feature quantity and hemodynamic parameters. The area features extracted by this method represent some of the most impo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/02
Inventor 杨承志刘贺张兴超吴端
Owner KUNMING UNIV OF SCI & TECH
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