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Electrocardio identity recognition method and system based on frequency domain cepstrum coefficient characteristics

A cepstral coefficient and identification technology, applied in the field of electrocardiographic identification, can solve the problems of easy false detection or missing detection, lack of adaptability, inability to deal with noise and signal spectrum overlap, etc., to avoid noise interference, good Recognition performance, effect of data processing volume reduction

Pending Publication Date: 2020-08-25
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Although the filter bank method has real-time performance, it cannot deal with the overlapping of noise and signal spectrum; the threshold discriminant method relies too much on the preprocessing of the signal, and if the signal is seriously disturbed by noise, it is easy to misdetect or miss detection; The transformation method has good anti-interference ability, but lacks adaptability

Method used

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  • Electrocardio identity recognition method and system based on frequency domain cepstrum coefficient characteristics
  • Electrocardio identity recognition method and system based on frequency domain cepstrum coefficient characteristics
  • Electrocardio identity recognition method and system based on frequency domain cepstrum coefficient characteristics

Examples

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Embodiment 1

[0032] This embodiment provides an electrocardiographic identification method based on frequency-domain cepstral coefficient features;

[0033] Such as figure 1 As shown, the ECG identification method based on frequency-domain cepstral coefficient features includes:

[0034] S101: Obtain an ECG signal to be identified;

[0035] S102: Preprocessing the ECG signal to be identified;

[0036] S103: Perform feature extraction on the preprocessed ECG signal to be identified, and extract features to be identified;

[0037] S104: Compare the features to be identified with the features in the ECG feature template library, and output an identification result.

[0038] As one or more embodiments, in the S101, the electrocardiogram signal to be identified is acquired; the specific steps include: acquiring by using electrodes or acquiring by using a wearable device.

[0039] It should be understood that those skilled in the art may select a specific collection method according to actua...

Embodiment 2

[0091] This embodiment provides an ECG identification system based on frequency-domain cepstral coefficient features;

[0092] ECG identification system based on frequency-domain cepstral coefficient features, including:

[0093] An acquisition module configured to: acquire an ECG signal to be identified;

[0094] A preprocessing module, which is configured to: preprocess the ECG signal to be identified;

[0095] A feature extraction module, which is configured to: perform feature extraction on the preprocessed electrocardiogram signal to be identified, and extract features to be identified;

[0096] The output module is configured to: compare the feature to be identified with the feature in the ECG feature template library, and output the identification result.

[0097] It should be noted here that the acquisition module, preprocessing module, feature extraction module and output module correspond to steps S101 to S104 in Embodiment 1, and the examples and application scena...

Embodiment 3

[0101] 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.

[0102] 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 frequency domain cepstrum coefficient characteristics. The method comprises the steps of obtaining an electrocardio signal to be recognized; preprocessing the electrocardiosignal to be recognized; performing feature extraction on the preprocessed to-be-recognized electrocardiosignals, and extracting to-be-recognized features; and comparing the to-be-identified features with features in an electrocardiogram feature template library, and outputting an identity identification result. The electrocardiosignalsare analyzed from the perspective of the frequency domain, compared with time domain analysis, all components of the signals can be found more visually, interference of noise is avoided, the extractedcepstrum coefficient serves as the characteristic of identity recognition, differences between different individuals can be well distinguished, and good recognition performance is achieved.

Description

technical field [0001] The present disclosure relates to the technical field of biological feature identification, in particular to a method and system for identifying ECG based on frequency-domain cepstral coefficient features. Background technique [0002] The statements in this section merely mention background art related to the present disclosure and do not necessarily constitute prior art. [0003] ECG signal, as a highly safe biological feature, has received widespread attention in recent years. This biological feature has obvious differences among different individuals. In addition to being used as a basis for disease diagnosis, it can also be used as a basis for disease diagnosis. Used for identification. In addition, ECG signals are generated in the human body and are difficult to be stolen or forged. Therefore, identification based on ECG signals (referred to as ECG identification) has a good development prospect. Common ECG signal feature extraction methods inc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00A61B5/00A61B5/04A61B5/0402
CPCA61B5/7235A61B5/316A61B5/318G06F2218/10G06F2218/04G06F2218/12
Inventor 杨公平王子欣黄玉文王奎奎尹义龙
Owner SHANDONG UNIV
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