Electrocardiogram signal feature detection algorithm based on wavelet transformation lifting and approximate envelope improving
A technology of feature detection and wavelet transform, applied in diagnostic recording/measurement, medical science, sensors, etc., can solve the problem that the ECG feature detection algorithm cannot take into account both detection accuracy and real-time Effect of Accuracy Improvement
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[0031] Specific embodiments of the present invention will be described in detail below in conjunction with technical solutions and accompanying drawings.
[0032] The invention is based on the lifting wavelet transform, the detection algorithm of the R wave, the starting and ending point of the QRS wave group, the P wave and the T wave position in the electrocardiogram signal of the improved approximate 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:
[0033] 1. Lifting wavelet improved semi-soft threshold denoising
[0034] 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 wavelet transform, the sym8 wavelet is selected as the wavelet basis function to perform three-layer lifting decomposition on the ECG signal, and the ...
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