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A method for analyzing heart rate variability data based on adaptive multiscale entropy

A heart rate variability and multi-scale entropy technology, applied in the medical field, can solve the problems that fixed-scale MSE cannot fully and accurately quantify HRV, and the number and size of scales are difficult to predict and estimate.

Active Publication Date: 2022-08-05
CHANGZHI MEDICAL COLLEGE
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Problems solved by technology

Therefore, the number of scales and their sizes are difficult to predict and estimate, and fixed-scale MSE cannot fully and accurately quantify HRV

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  • A method for analyzing heart rate variability data based on adaptive multiscale entropy
  • A method for analyzing heart rate variability data based on adaptive multiscale entropy
  • A method for analyzing heart rate variability data based on adaptive multiscale entropy

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[0053] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention clearer, the present invention will be further described in detail with reference to the embodiments and the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention. The technical solutions of the present invention will be described in detail below with reference to the embodiments and the accompanying drawings, but the protection scope is not limited by this.

[0054] This embodiment is a method for analyzing heart rate variability data based on adaptive multi-scale entropy AMSE: the AMSE method first performs IMMD adaptive decomposition on the data to obtain a series of multi-scale mean substitution data sets of the original data; secondly, the mean substitution data Each element in the set is coarse-grained and its correspon...

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Abstract

The invention belongs to the field of medical technology, and relates to a method for analyzing heart rate variability data based on self-adaptive multi-scale entropy; the invention overcomes the shortcomings of MSE quantifying HRV complexity in a fixed scale, and quantifies HRV complexity comprehensively and accurately; The HRV is adaptively decomposed by state decomposition, and a series of multi-scale mean substitution data sets of the original data are obtained; secondly, each element in the mean substitution data set is coarse-grained and the corresponding adaptive scale is obtained; finally, the coarse-grained calculation is carried out. The averaged value replaces the SampEn value of each element in the data set, and the adaptive multi-scale entropy is obtained; the adaptive multi-scale entropy can comprehensively and accurately evaluate the HRV complexity.

Description

technical field [0001] The invention relates to the field of medical technology, in particular to a method for analyzing heart rate variability data based on adaptive multi-scale entropy. Background technique [0002] Heart rate variability (HRV) is the temporal variation between successive cardiac cycles (N-N or R-R). HRV contains rich information on individual cardiovascular regulation, reflecting that sinus node autoregulation is influenced by sympathetic nerve, vagus nerve, central nervous system, carotid artery pressure and chemoreceptors and other physiological aspects. By detecting and analyzing HRV, diseases related to autonomic nerve function, such as coronary heart disease, heart failure, hypertension, etc., can be assessed. [0003] HRV analysis methods are generally divided into linear and nonlinear analysis methods. Linear analysis methods include: statistical analysis or geometric graphic analysis of HRV data in the time domain, and HRV-based spectrum analysi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/024A61B5/00G06F17/18
CPCA61B5/02405A61B5/72G06F17/18
Inventor 牛晓东卢莉蓉王鉴李璇刘婷王黎明
Owner CHANGZHI MEDICAL COLLEGE
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