Electrocardiosignal characteristic detection algorithm

An ECG signal and feature detection technology, applied in the field of medical signal processing, can solve the problem that the ECG feature detection algorithm cannot take into account the detection accuracy and real-time performance at the same time, so as to improve the R-wave detection accuracy, the detection accuracy and the detection accuracy. Effect

Inactive Publication Date: 2014-04-30
TIANJIN POLYTECHNIC UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to solve the problem that the current ECG feature detection algorithm cannot take into account the detection acc...

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  • Electrocardiosignal characteristic detection algorithm
  • Electrocardiosignal characteristic detection algorithm
  • Electrocardiosignal characteristic detection algorithm

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Embodiment Construction

[0024] Specific embodiments of the present invention will be described in detail below in conjunction with technical solutions and accompanying drawings.

[0025] The present invention proposes an ECG signal preprocessing method based on lifting wavelet transform combined with an improved approximate envelope, and designs an ECG signal detection algorithm based on the slope threshold of R wave, QRS wave group starting and ending points, P wave and T wave position, figure 2 It is a specific flow chart of ECG signal preprocessing and R wave detection, and the specific implementation steps are:

[0026] 1. Preprocessing of ECG signals

[0027] According to the characteristic waveform of the ECG signal and the frequency domain distribution characteristics of the noise, using the time-frequency local characteristics of the lifting wavelet transform, the sym8 wavelet is selected as the wavelet basis function to carry out five-layer lifting decomposition of the ECG signal, extract h...

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Abstract

The invention discloses an electrocardiosignal characteristic detection algorithm, and provides an electrocardiosignal preprocessing algorithm combining an improved lifting wavelet threshold and an improved approximate enveloping algorithm. Compared with wavelet denoising, improved lifting wavelet threshold denoising has the advantages that the signal processing time is shortened, the signal-to-noise ratio is increased, the design of an envelope function is improved, and other characteristic waves except R waves and the energy of noise are suppressed while the R-wave energy is enhanced. The characteristic detection algorithm based on a slope threshold is designed, and detection of R waves, P waves and T waves is performed respectively. The detection algorithm is simple and quick, and is suitable for parallel processing. The occupied memory space is small, and the R-wave detection rate can be up to 99.8 percent.

Description

technical field [0001] The invention belongs to the technical field of medical 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. The prevention and diagnosis of heart disease has become one of the most important problems to be solved urgently in the medical field today. One of the main technologies used to diagnose heart disease is the electrocardiogram. For more than 100 years, the electrocardiogram, a non-invasive examination technique, has played an important role in the diagnosis of heart disease due to its advantages of simple diagnostic methods and no harm to patients. Conventional ECG monitors or ECG workstations commonly used in hospitals at present have the disadvantages of large size, high price, and inconvenient monitoring at any time. Alt...

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Application Information

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IPC IPC(8): A61B5/0452
Inventor 李鸿强陈磊冯秀丽王小飞梁欢陈雪龙
Owner TIANJIN POLYTECHNIC UNIV
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