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A Pulse Signal Feature Extraction Method Based on Multiwavelet Transform Fusion

A multi-wavelet transform, pulse signal technology, applied in medical science, diagnosis, catheter and other directions, can solve the problems of inaccurate results, inaccurate pulse wave cycle division and feature extraction, etc.

Active Publication Date: 2019-03-26
BEIJING INSTITUTE OF TECHNOLOGYGY +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] The present invention aims to solve the problem that in the process of using wavelet transform to denoise the pulse wave signal, only one of the wavelet base functions is selected for denoising, resulting in inaccurate results, and the periodical division and feature extraction of the pulse wave are not accurate enough. A pulse signal feature extraction method based on multi-wavelet transform fusion is proposed

Method used

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  • A Pulse Signal Feature Extraction Method Based on Multiwavelet Transform Fusion
  • A Pulse Signal Feature Extraction Method Based on Multiwavelet Transform Fusion
  • A Pulse Signal Feature Extraction Method Based on Multiwavelet Transform Fusion

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Embodiment 1

[0095] This embodiment describes the process of applying the "a pulse signal feature extraction method based on multi-wavelet transform fusion" of the present invention to pulse wave detection and feature extraction scenarios.

[0096] figure 1 Be the flowchart of this method and the flowchart of this embodiment, as can be seen from the figure, this method comprises the following steps:

[0097] Step A: Use the wavelet basis function ψ i (t) Perform wavelet transformation and threshold processing on the original pulse wave signal x[n] through formulas (1)~(5) and perform wavelet reconstruction to obtain the pulse wave signal f denoised using the wavelet basis function k [n].

[0098] Specifically, the value of i in this example is 4, and the wavelet basis function ψ 1 (t) Select sym8 wavelet, wavelet basis function ψ 2 (t) Select sym4 wavelet, wavelet basis function ψ 3 (t) Select db6 wavelet, wavelet basis function ψ 4 (t) select db4 wavelet; obtain 4 pulse wave signals...

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Abstract

The invention discloses a pulse signal characteristic extraction method based on multi-wavelet transform fusion and belongs to the technical field of noise processing and signal characteristic extraction. At a data preprocessing state, a final denoised pulse wave is obtained with a weighting method according to multiple results of denoising based on multiple wavelet basis functions, wavelet transform is performed on the basis of Shannon's theorem and first-order derivative of Gaussian function, main wave location of the pulse wave is searched, cycle division is carried out, further, the divided cycle is subjected to wavelet packet decomposition and high-order statistic calculation, and accordingly, the characteristic quantity is obtained. According to the method, multiple denoised resultscan be integrated effectively, accuracy of multi-wavelet transform denoising is improved, and precision of main wave extraction and accuracy of pulse wave characteristic quantity extraction are improved.

Description

technical field [0001] The invention relates to a pulse signal feature extraction method based on multi-wavelet transform fusion, and belongs to the technical field of noise processing and signal feature extraction. Background technique [0002] The human pulse wave signal contains rich physiological information of the human body. Its detection and analysis under modern medical technology can effectively obtain information about the physiological state and pathological changes of the human body. However, due to baseline drift, power frequency interference and myoelectric interference, etc. In the presence of noise, the required pulse wave may be submerged in it and cannot be collected. At present, in some related studies, methods such as Fourier transform and band-pass filtering are used to remove noise, and wavelet transform is more suitable for use than the previous method due to its good localization properties in both time domain and frequency domain. For noise eliminat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/02A61B5/00
CPCA61B5/02A61B5/7203A61B5/725A61B5/7253
Inventor 郭树理韩丽娜李灵甫桂心哲陈启明张祎彤刘宏斌范利骆雷鸣
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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