Pulse condition classification method based on salient signal sub-segment extraction

A classification method, sub-segment technology, applied in the field of medical diagnosis

Active Publication Date: 2020-11-10
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] The purpose of the present invention is in order to solve the problem of pulse condition classificati...

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  • Pulse condition classification method based on salient signal sub-segment extraction
  • Pulse condition classification method based on salient signal sub-segment extraction
  • Pulse condition classification method based on salient signal sub-segment extraction

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Embodiment Construction

[0053] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0054] Such as figure 1 As shown, the present invention provides a kind of pulse condition classification method based on significant signal subsection extraction, comprises the following steps:

[0055] S1: Use a Doppler ultrasonic blood analyzer to collect pulse signals and perform preprocessing to obtain c pulse signal training samples;

[0056] S2: Locating the position indicator vectors of the significant pulse signal sub-segments of the c pulse signal training samples;

[0057] S3: Construct a multimodal distance feature vector according to the position indicator vector of the significant pulse signal sub-segment;

[0058] S4: According to the multimodal distance feature vector, the nearest neighbor classifier is used to classify the pulse signal, and the pulse classification based on the extraction of significant signal sub-segments is completed...

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Abstract

The invention discloses a pulse condition classification method based on salient signal sub-segment extraction, and the method comprises the steps: S1, collecting pulse signals, carrying out the preprocessing, and obtaining c pulse signal training samples; s2, positioning a significant pulse signal sub-segment position indication vector; s3, constructing a multi-modal distance feature vector; andS4, classifying the pulse signals by adopting a nearest neighbor classifier to finish pulse condition classification based on significant signal sub-segment extraction. According to the pulse condition classification method, periodic segmentation does not need to be conducted on the pulse signals, the sub-segments with distinguishing force are extracted from the pulse signals, information redundancy is avoided, and the subsequent calculation process can be accelerated. Characteristic information complementation can be achieved by constructing the multi-modal distance characteristic vectors ofthe signal subsections, pulse signal classification accuracy can be improved, automatic pulse condition recognition is achieved, auxiliary decisions are provided for pulse diagnosis of doctors, and the extracted pulse signal subsections can provide interpretable results for further clinical analysis.

Description

technical field [0001] The invention belongs to the technical field of medical diagnosis, and in particular relates to a pulse condition classification method based on significant signal sub-segment extraction. Background technique [0002] In the clinical diagnosis of traditional Chinese medicine, doctors of traditional Chinese medicine feel the pulse at the radial artery of the wrist with their fingers, and judge the patient's health status according to the speed, strength and depth of the pulse. However, the description of the concept of pulse condition in traditional Chinese medicine is relatively vague, so the identification standard of pulse condition is not clear, and the accuracy of syndrome differentiation depends to a large extent on the experience of doctors. has a difference. This traditional method of pulse diagnosis, which relies entirely on the subjective experience of doctors, will limit the promotion and inheritance of TCM pulse diagnosis technology. There...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G16H50/20
CPCG16H50/20G06F2218/04G06F2218/12G06F18/2411G06F18/214
Inventor 李巧勤肖迪尹刘勇国杨尚明
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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