A method for detecting r-characteristic wave of electrocardiographic signal

A technology of ECG signal and detection method, applied in diagnostic recording/measurement, medical science, sensor, etc., which can solve the problem of poor processing

Active Publication Date: 2014-10-15
HEBEI UNIVERSITY
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Problems solved by technology

[0003] The purpose of the present invention is to provide a kind of electrocardiographic signal R characteristic wave detection method, to solve the poor problem of existing analysis algorithm in dealing with high-frequency noise and QRS complex form change

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  • A method for detecting r-characteristic wave of electrocardiographic signal
  • A method for detecting r-characteristic wave of electrocardiographic signal
  • A method for detecting r-characteristic wave of electrocardiographic signal

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Embodiment 1

[0043] This embodiment is implemented in a computer with Intel Pentium Dual E2200 2.20GHz, internal memory of 3.00GB, and operating system of Window XP. The entire R-wave detection algorithm is written in Matlab language.

[0044] The implementation process of the present invention is as figure 1 Shown:

[0045] a) ECG signal acquisition and output: use the ECG signal acquisition equipment (the seven-lead synchronous electrocardiogram module (ECG CB) of Beijing Mactron Electronic Instrument Co., Ltd., the sampling frequency is 250HZ, the length of the analysis time interval of the ECG signal It is set to 10s) to collect the ECG signal of the human body and store it in the form of TXT. In the Matlab software, read the ECG data in the TXT file into the environment, such as figure 2 , to obtain the original ECG signal.

[0046] b) Using the improved threshold wavelet decomposition method to filter the original ECG signal:

[0047] b-1) Select the DB6 wavelet of the Daubechie...

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Abstract

The invention discloses a method for detecting the R characteristic wave of an electrocardiogram signal. The collected electrocardiogram signal is filtered by a wavelet decomposition method with an improved threshold value, and then the wavelet reconstruction for highlighting the QRS wave group is performed to analyze the energy from the time domain. Energy window transformation of domain analysis, then select the maximum point and optimize it, and finally select the R wave according to the R wave selection logic. The present invention uses the multi-resolution characteristic of wavelet analysis to decompose the signal into different scales according to the frequency, thereby processing the signals on different scales in a targeted manner, increasing the flexibility of the algorithm; adopting the method of energy window transformation, The signal is transformed from the time domain to the energy domain, which effectively suppresses the interference of high-frequency noise and improves the stability of the algorithm; through wavelet reconstruction, the QRS wave group is extracted, and the P wave and T wave are removed as noise , It effectively avoids false detection caused by tall P waves and T waves in the detection process, and improves the detection accuracy.

Description

technical field [0001] The invention relates to the technical field of automatic detection and analysis of electrocardiographic signals, in particular to a method for detecting R characteristic waves of electrocardiographic signals. Background technique [0002] Heart disease is hidden and latent, and it is difficult to show it on the ECG when it does not occur, and it is short-lived when it occurs, and it is too late to observe the ECG. For this reason, it is necessary to carry a 24-hour Holter to the patient for 24-hour ECG signal collection. However, this will result in a huge amount of data, and doctors need a lot of time to check the ECG one by one to find abnormal points, which greatly increases the burden on doctors. At the same time, the diagnosis process will be affected by personal cognition and emotion, making the diagnosis of heart disease subjective. This deviation can be corrected by applying automatic analysis technology of electric signal. The existing ana...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/0456A61B5/352
Inventor 刘秀玲杨建利董斌王洪瑞
Owner HEBEI UNIVERSITY
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