R wave detection algorithm based on extremum field mean mode decomposition and improved Hilbert enveloping

A detection algorithm and pattern decomposition technology, applied in diagnostic recording/measurement, medical science, sensors, etc., can solve the problems of large data endpoint swing, complex wavelet base, and lack of mean value, etc., to improve detection accuracy and reduce decomposition layer Number, the effect of increasing the decomposition speed

CN103190901AInactive Publication Date: 2013-07-10TIANJIN POLYTECHNIC UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2013-07-10
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses an R wave detection algorithm based on extremum field mean mode decomposition and improved Hilbert enveloping and belongs to the technical field of weak biological signal processing. An electrocardio signal pre-processing algorithm based on the extremum field mean mode decomposition and the improved Hilbert enveloping and an R wave detection algorithm based on slope threshold are provided. Detection criteria are set according to wave form characteristics and time domain distribution characters of electrocardio signals, and positions of R waves with most obvious characters and highest information amount in the electrocardio signals are detected. An extremum field mean mode decomposition algorithm improves empirical mode decomposition speed and can effectively restrain mode superimposition and boundary effect. The improved Hilbert enveloping can effectively restrain interference of noise and other characteristic waves an can also enhance energy of the R waves. The R wave detection algorithm based on the extremum field mean mode decomposition and the improved Hilbert enveloping can also detect positions of R points accurately even if interference of strong noise and large P / T waves exists. A Massachusetts institute of technology-Beth Israel hospital (MIT-BIH) data base is used for detecting the R wave detection algorithm. Sensitivity of the R wave detection algorithm is 99.94%, and positive predictive rate is 99.87%.
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Description

technical field

[0001] The invention belongs to the technical field of weak bioelectrical signal processing, in particular to the denoising of weak electrocardiographic signals interfered by severe noise and the detection of feature points. Background technique

[0002] Heart disease is one of the diseases with the highest morbidity and mortality in medicine today, and the prevention and diagnosis of heart disease is the primary problem facing the medical field today. One of the main technologies for diagnosing heart disease is electrocardiogram (ECG). Because the method of diagnosing heart disease and cardiovascular disease by electrocardiogram is non-invasive, it is convenient and easy to perform electrocardiogram diagnosis and has been widely used clinically. The ECG signals collected by non-invasive body surface electrodes are relatively weak, only at the millivolt level, so the ECG signals are easily interfered by the external environment. These interferences include p...

Examples

Embodiment Construction

[0028] Specific embodiments of the present invention will be described in detail below in conjunction with technical solutions and accompanying drawings.

[0029] The present invention is based on the detection algorithm of the R wave in the electrocardiogram signal based on filtering, extreme value domain mean mode decomposition, improved Hilbert envelope and slope threshold, figure 2 It is a specific flow chart of ECG signal preprocessing and R wave detection, and the specific implementation steps are:

[0030] 1. Butterworth low-pass filter

[0031] According to the characteristic waveform of the electrocardiographic signal and the frequency domain distribution characteristics of the noise, first utilize the Butterworth low-pass filter to filter out the high-frequency noise in the electrocardiographic signal, the present invention sets the cut-off frequency of the Butterworth low-pass filter to be 35Hz, Can retain more than 90% of the QRS wave energy and most of the P wav...