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Electrocardio T-wave feature extraction method based on fractional Fourier transform and tensor decomposition

A technology of fractional Fourier and tensor decomposition, applied in diagnostic recording/measurement, medical science, diagnosis, etc.

Active Publication Date: 2021-03-26
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Abstract
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  • Claims
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Problems solved by technology

However, because the T wave is very weak, a small amount of noise may have completely covered the T wave, so part of the T wave may be removed during the noise removal process

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  • Electrocardio T-wave feature extraction method based on fractional Fourier transform and tensor decomposition
  • Electrocardio T-wave feature extraction method based on fractional Fourier transform and tensor decomposition
  • Electrocardio T-wave feature extraction method based on fractional Fourier transform and tensor decomposition

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Embodiment Construction

[0039] The present invention will be described in detail below, and the technical problems and beneficial effects solved by the technical solutions of the present invention are also described. It should be pointed out that the described examples are only intended to facilitate the understanding of the present invention, and do not have any limiting effect on it. .

[0040] The specific implementation manner of the present invention will be described below by taking the TWA phenomenon detection as an example, with reference to the accompanying drawings. Algorithm flow chart see figure 1 . The databases used include PhysioNet: T-Wave Alternans Challenge Database and MIT-BIH Normal Sinus Rhythm Database.

[0041]From the PhysioNet: T-Wave Alternans Challenge Database, the numbers are 01, 06, 09, 13, 15, 17, 21, 25, 28, 29, 30, 33, 34, 35, 50, 51, 64, 67, 69, 70, 72, 73, 76, 79, 82, 88, 91, 97, 98 A total of 29 ECG signal data including TWA, ECG contains 12 channels of records ...

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Abstract

The invention discloses an electrocardio T-wave feature extraction method based on fractional Fourier transform and tensor decomposition, and belongs to the field of electrocardio signal processing. According to the method, electrocardio of a plurality of heart beats is continuously processed, fractional Fourier transform is adopted to perform dimension expansion on T-wave data of each heart beatto obtain a T-wave matrix, the T-wave matrix of the continuous heart beats is used to construct a third-order tensor, projection components in a third direction are obtained through Tucker decomposition, entropy values of the projection components are taken as features of electrocardio T-waves of the section, electrocardiosignal classification can be carried out through combination with machine learning, and particularly, a TWA phenomenon can be detected.

Description

technical field [0001] The invention proposes a method for extracting features of electrocardiographic signals, which is suitable for combining suitable classifiers, establishing classification models, and detecting abnormal electrocardiograms, especially T wave abnormalities, and belongs to the field of electrocardiographic signal processing. Background technique [0002] Surface electrocardiogram (ECG) is the most common non-invasive detection method of heart status, and abnormal ECG is closely related to the occurrence of malignant arrhythmia. Based on the electrocardiogram T-wave alternation (T-wave alternate, TWA) phenomenon, because its basic mechanism has a corresponding relationship with malignant arrhythmia in clinical practice, it is currently considered as a non-invasive electrophysiological test that has an important predictive effect on malignant arrhythmia. index. [0003] T-wave alternation (T-wave Alternant.TWA) refers to a kind of ECG variation phenomenon i...

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Application Information

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IPC IPC(8): A61B5/318A61B5/366A61B5/352A61B5/355A61B5/00
CPCA61B5/7225A61B5/7203A61B5/7257A61B5/7267
Inventor 辛怡赵淑丽葛传斌刘娟
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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