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Detection method of electrocardiosignal R characteristic waves

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

Active Publication Date: 2013-06-19
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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  • Detection method of electrocardiosignal R characteristic waves
  • Detection method of electrocardiosignal R characteristic waves
  • Detection method of electrocardiosignal R characteristic waves

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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 detection method of electrocardiosignal R characteristic waves. A wavelet decomposition method for improving threshold value is carried out on collected electrocardiosignals to conduct filtering, then wavelet reconstruction protruding out of a QRS wave group is carried out, energy window conversion from time domain analysis to energy domain analysis is carried out, then a maximum value point is selected and optimized, and finally an wave selection is carried out according to R selection logics. The detection method uses multiresolution characteristics of wavelet analysis to decompose signals on different scales according to frequency to accordingly process the signals on the different scales in a targeted mode and increase algorithmic flexibility. The energy window conversion method is adopted to convert the signals from a time domain to an energy domain, effectively restrains interference of high-frequency noise and improves algorithmic stability. By means of wavelet reconstruction, the QRS wave groups are extracted, P waves and T waves serve as noise to be rejected, false detection caused by huge P waves and T waves in detection can be effectively avoided, and detection accuracy is improved.

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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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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