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Electrocardio identity recognition method and system based on local constraint non-negative matrix factorization

A technology of non-negative matrix decomposition and local constraints, which is applied in the field of identification to achieve the effect of improving the recognition effect

Active Publication Date: 2021-03-05
SHANDONG UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, although the identification technology based on ECG signals has some advantages, there are still many difficulties to be overcome in the existing identification technology.

Method used

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  • Electrocardio identity recognition method and system based on local constraint non-negative matrix factorization
  • Electrocardio identity recognition method and system based on local constraint non-negative matrix factorization
  • Electrocardio identity recognition method and system based on local constraint non-negative matrix factorization

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0031] This embodiment provides an electrocardiogram identification method based on non-negative matrix factorization of local constraints;

[0032] Such as figure 1 As shown, the ECG identification method based on non-negative matrix factorization with local constraints includes:

[0033] S101: Obtain an ECG signal to be identified;

[0034] S102: Divide the electrocardiographic signal to be identified into heart beats to obtain several single-period electrocardiographic signals;

[0035] S103: For each single-period ECG signal, project the ECG signal from a high-dimensional space to a low-dimensional space by using the pre-acquired pseudo-inverse matrix of the basis matrix to obtain a feature representation after dimensionality reduction;

[0036] Wherein, the pseudo-inverse matrix of the pre-acquired base matrix is ​​obtained by processing the ECG signal training data set through a non-negative matrix decomposition method based on local constraints;

[0037] S104: Input ...

Embodiment 2

[0089] This embodiment provides an electrocardiographic identification system based on non-negative matrix factorization of local constraints;

[0090] ECG identification system based on non-negative matrix factorization with local constraints, including:

[0091] An acquisition module configured to: acquire an ECG signal to be identified;

[0092] A division module, which is configured to: divide the electrocardiographic signal to be identified into heart beats to obtain several single-period electrocardiographic signals;

[0093] A projection module, which is configured to: for each single-period ECG signal, use the pre-acquired pseudo-inverse matrix of the basis matrix to perform projection, project the ECG signal from the high-dimensional space to the low-dimensional space, and obtain the feature after dimensionality reduction express;

[0094] Wherein, the pseudo-inverse matrix of the pre-acquired base matrix is ​​obtained by processing the ECG signal training data set ...

Embodiment 3

[0100] This embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein, the processor is connected to the memory, and the one or more computer programs are programmed Stored in the memory, when the electronic device is running, the processor executes one or more computer programs stored in the memory, so that the electronic device executes the method described in Embodiment 1 above.

[0101] It should be understood that in this embodiment, the processor can be a central processing unit CPU, and the processor can also be other general-purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic devices , discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, o...

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Abstract

The invention discloses an electrocardio identity recognition method and system based on local constraint non-negative matrix factorization. The method comprises the steps that an electrocardio signalto be recognized is obtained; heart beat division is carried out on the to-be-recognized electrocardiosignals to obtain a plurality of single-cycle electrocardiosignals; the method also includes projecting each single-cycle electrocardiosignal by using a pseudo-inverse matrix of a pre-acquired basis matrix, and projecting the electrocardiosignal from a high-dimensional space to a low-dimensionalspace to obtain feature representation after dimension reduction, wherein the pre-acquired pseudo-inverse matrix of the basis matrix is acquired by processing the electrocardiosignal training data setthrough a non-negative matrix decomposition mode based on local constraints; and inputting the feature representation after dimension reduction into the trained classification model to obtain an identity recognition result corresponding to the current to-be-recognized electrocardiosignal.

Description

technical field [0001] The present application relates to the technical field of identification, in particular to an ECG identification method and system based on local constraint non-negative matrix decomposition. Background technique [0002] The statements in this section merely mention the background art related to this application, and do not necessarily constitute the prior art. [0003] In recent years, the universality and discriminability of ECG signals have been widely concerned and applied to identity recognition. The ECG signal is an important physiological signal in the human body. There are differences between different individuals. The ECG signal will not change greatly in a continuous period of time. With the development of micro-sensor technology, the ECG signal Collection is also more convenient. Therefore, the ECG signal has the characteristics of universality, distinguishability, stability, and easy collection, which meets the premise of biometric ident...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06F2218/04G06F2218/12G06F2218/08G06F18/2411G06F18/214
Inventor 杨公平盛怡璇孙启玉刘玉峰张永忠
Owner SHANDONG UNIV
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