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ECG identity recognition method based on t-SNE and Adaboost

An identity recognition and algorithm technology, applied in character and pattern recognition, pattern recognition in signals, instruments, etc., can solve problems such as large amount of calculation and insufficient recognition accuracy

Active Publication Date: 2021-01-22
JILIN UNIV +1
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Problems solved by technology

[0007] The purpose of the present invention is to provide an ECG identification method based on t-SNE and Adaboost in order to solve the problems that the current ECG identification technology is facing a large amount of calculation and insufficient identification accuracy

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  • ECG identity recognition method based on t-SNE and Adaboost
  • ECG identity recognition method based on t-SNE and Adaboost
  • ECG identity recognition method based on t-SNE and Adaboost

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Embodiment Construction

[0070] The concept, technical solutions and advantages of the present invention will be clearly and completely described below in conjunction with specific embodiments and accompanying drawings, so as to fully understand the purpose, solutions and effects of the present invention.

[0071] figure 1 It is a schematic flow chart of the ECG identification method. combine figure 1 , the steps of the ECG identification method based on t-SNE and Adaboost in the described embodiment are as follows:

[0072] S100. Obtain a sample data set of electrocardiogram signals including multiple heart beats of multiple individuals as raw signal data for extracting features and training a classifier.

[0073] S200. Using a median filter and a wavelet denoising algorithm, remove baseline drift, power frequency interference, and myoelectric noise in the ECG signal sample data set.

[0074] S300. Using a high-power signal enhancement method, perform R-point positioning, cardiac beat segmentation...

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Abstract

The invention discloses an ECG identity recognition method based on t-SNE and Adaboost, and the method comprises the steps: 1, removing noise through a median filter and a wavelet denoising algorithm;2, obtaining a plurality of single-cycle cardiac beat data; 3, obtaining a feature vector of the single-cycle cardiac beat data; 4, adopting an Adaboost algorithm to construct and train a classifier;and 5, finally outputting an identification result, i.e., the individual identity in the database corresponding to the electrocardiosignal data. The ECG identity recognition method has the advantagesthat the dimensionality of ECG signal data processing can be greatly reduced, the training speed of a classifier is increased, meanwhile, information and category labels of ECG signal data are effectively utilized, and the accuracy and timeliness of ECG identity recognition are enhanced. Meanwhile, the t-SNE algorithm and the Adaboost are combined to form an efficient strong classifier, and the universality and accuracy of the identity recognition method are improved.

Description

technical field [0001] The invention relates to an ECG identification method, in particular to an ECG identification method based on t-SNE and Adaboost. Background technique [0002] At present, with the rapid development of information technology, personal identification technology has been widely used in fields such as finance, medical care, security monitoring and data confidentiality. However, traditional identification technologies such as certificates, passwords, and passwords have defects such as being easily copied, stolen, and forgotten. Therefore, identification technologies based on human biometrics have emerged as the times require. Biometric identification uses the unique physiological or behavioral characteristics of each person, such as fingerprints, irises, voiceprints, facial features, gait features, etc. Compared with traditional identification and authentication methods, it has a greater Advantage. [0003] However, there are some defects in the above bi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06F2218/04G06F2218/12
Inventor 司玉娟冯文轩杨维熠孙美琪刘鑫
Owner JILIN UNIV
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