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Sinus heart rate turbulence trend detection method based on piecewise linearization

A sinus heart rate oscillation, piecewise linearization technology, applied in the field of biomedical signal processing, can solve the problem of easy missed detection of ECG signals, and achieve the effect of being suitable for real-time processing, simple implementation, and reducing false detection.

Inactive Publication Date: 2013-04-03
SHANDONG NORMAL UNIV
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Problems solved by technology

This method is easy to miss detection of ECG signals with small amplitude

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  • Sinus heart rate turbulence trend detection method based on piecewise linearization
  • Sinus heart rate turbulence trend detection method based on piecewise linearization
  • Sinus heart rate turbulence trend detection method based on piecewise linearization

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[0078] 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.

[0079] A kind of sinus heart rate oscillation trend detection method based on piecewise linearization, comprising the following steps:

[0080] (1) ECG signal preprocessing: ECG signal sampling frequency conversion, removal of baseline drift, power frequency fundamental wave and its harmonic interference, and myoelectric interference in the ECG signal;

[0081] (2) Self-learning process in the first 10 seconds: establish a normal heartbeat template, calculate the mean square error wch(i) of all sinus heartbeats and heartbeat templates in this 10-second data, and take the maximum value of wch times the template threshold thbeat, ie Establish the RR interval threshold, take 4 / 5 of the average value of 8 RR intervals as the RR inter...

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Abstract

The invention discloses a sinus heart rate turbulence trend detection method based on piecewise linearization. The piecewise linearization is adopted for specifically analyzing whether the variation trend of sinus heart rate accelerates first and then decelerates after premature ventricular contractions or not. The method includes the steps: (1) electrocardiosignal preprocessing; (2) self-learning process for first 10 seconds; (3) HRT (heart rate turbulence) sample collection; (4) piecewise trend analysis; and (5) turbulence trend representation based on a cloud model. The variation trend of the sinus heart rate at the RR interval is detected by means of piecewise linearization, and the turbulence trend is further represented by natural language through the cloud model. By the aid of an MATLAB (matrix laboratory) simulation tool, signals in an MIT-BIH heart beat irregularity database are selected for verification, and the variation trend of the sinus heart rate after single-time ventricular premature beat can be detected correctly. In addition, using the exponential smoothing method to predicate QRS complex occurrence positions to facilitate detection of QRS complex, and using a template for judging sinus heart beat is simple to implement and suitable for real-time treatment.

Description

technical field [0001] The invention relates to a detection method, in particular to a detection method of sinus heart rate oscillation trend based on segmental linearization. It belongs to the technical field of biomedical signal processing. Background technique [0002] Heart rate turbulence (Heart rate turbulence, HRT) refers to the phenomenon that the sinus heart rate first accelerates after a premature ventricular contraction (ventricular premature) with compensatory pauses, and then the sinus heart rate decelerates, with biphasic fluctuations. feature. The evaluation of autonomic nervous activity has important clinical significance. HRT is the rapid regulatory response of the autonomic nervous system to the fluctuation of arterial blood pressure after a single premature ventricular contraction, and can evaluate the integrity and stability of the autonomic nervous system. At present, in terms of clinical application, HRT has been affirmed as a predictor of mortality a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0472A61B5/366
Inventor 赵捷尹文枫陈甜甜
Owner SHANDONG NORMAL UNIV
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