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Heart rate turbulence tendency extraction method based on cloud model and scatter diagram

A technology for sinus heart rate oscillation and trend extraction, which is applied in the field of biomedical signal processing and can solve the problems of ignoring the overall characteristics and the PLR ​​method does not guarantee that the time series has only one basic trend.

Inactive Publication Date: 2013-09-04
SHANDONG NORMAL UNIV
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Problems solved by technology

The residual-based PLR method does not guarantee that there is only one basic trend in each segment of the time series, and only focuses on local features while ignoring the overall features

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  • Heart rate turbulence tendency extraction method based on cloud model and scatter diagram
  • Heart rate turbulence tendency extraction method based on cloud model and scatter diagram
  • Heart rate turbulence tendency extraction method based on cloud model and scatter diagram

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be noted that the following description is only for explaining the present invention and not limiting its content.

[0038]According to the unified requirements of the portable ECG monitoring system, the present invention uniformly converts the sampling frequency of ECG signals used in the MIT-BIH database of the Massachusetts Institute of Technology from 360 Hz to 200 Hz through interpolation extraction. For the baseline drift, power frequency fundamental wave and its harmonic interference, myoelectric interference, etc. contained in the electrocardiographic signal, the present invention uses bior2.2 wavelet to perform three-layer decomposition and reconstruction combined with an improved threshold algorithm to eliminate them. Then, the bior2.2 wavelet was used to decompose the ECG signal into three layers to detect the R wave, and the HRT sampl...

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Abstract

The invention discloses a heart rate turbulence tendency extraction method based on a cloud model and a scatter diagram. The heart rate turbulence tendency extraction method based on the cloud model and the scatter diagram comprises the specific steps of (1) collecting HRT samples, (2) drawing the Poincare scatter diagram of RR intervals, dividing coupling points into two types of coupling points, matching the two types of the coupling points with a decelerating cloud and an accelerating cloud, and determining two ortho-state cloud curvilinear equations through a reverse-cloud generator, (3) finding critical points of two types of the coupling points, calculating linear regression slopes section by section, and storing slope vectors, (4) calculating tj_mean when changes of types continuously happen on adjacent k coupling points, and substituting the tj_mean into the two ortho-state cloud curvilinear equations to calculate the degree of membership, (5) comparing a sign yun with a subsection slope before k coupling points, comparing the sign yun and a subsection slope after the k coupling points, and classifying the k coupling points into a front subsection or a later subsection, (6) updating subsection points, calculating the linear regression slopes section by section, and updating the slope vectors, (7) mixing adjacent subsections together when the adjacent subsections are the same in sign of slopes, and repeatedly carrying out the step (6) until adjacent subsections needing to be mixed together do not exist.

Description

technical field [0001] The invention relates to a sinus heart rate oscillation trend extraction method, in particular to a sinus heart rate oscillation trend extraction method based on a cloud model and a scatter diagram. The invention belongs to the technical field of biomedical signal processing. Background technique [0002] 1. Sinus heart rate oscillation detection [0003] Sinus heart rate turbulence (heart rate turbulence, HRT) refers to the phenomenon that the sinus heart first accelerates and then decelerates after a ventricular premature contraction (premature contraction) with compensatory pauses, and is an important index for risk stratification of cardiovascular diseases one. Basic detection method: The most commonly used equipment is the dynamic electrocardiogram (Hoher) instrument, which usually records continuously for 24 hours. The continuous recording of a single premature ventricular contraction with sinus rhythm before and after the premature contraction...

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Application Information

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IPC IPC(8): A61B5/0452
Inventor 赵捷尹文枫
Owner SHANDONG NORMAL UNIV
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