Identity recognition method based on PPG signal sparse decomposition

Abstract

The invention discloses an identity recognition method based on PPG signal sparse decomposition. The method comprises following steps: step one, obtaining a PPG signal of a person to be identified, and preprocessing the PPG signal by filtering, moving average, and zero-mean methods; step two, detecting the time domain features of the preprocessed signal to extract the time domain feature value andextracting the optimal waveband of the preprocessed signal; step three, cutting the waveform of extracted optimal waveband to obtain a plurality of monocycle waveforms; step four, carrying out signalsparse decomposition on the monocycle waveforms to obtain optimal atomic feature parameter characteristics of the signal; step five, using the time domain feature value and the optimal atomic featureparameter characteristics to carry out feature fusion to obtain a training template and a test sample; and step six, utilizing a support vector machine to match the test sample and the training template to identify the identity of the person. The provided method solves the problem that in the prior art, a conventional identity recognition method is easily influenced by the external environment and the operation is complicated. The recognition rate of the method can reach 98% or more.

Description

technical field [0001] The invention belongs to the technical field of information processing, and in particular relates to an identity recognition method based on sparse decomposition of PPG signals. Background technique [0002] With the rapid development of information security technology, people's requirements for the security, convenience and efficiency of identification are constantly increasing, and traditional information security protection measures such as complex digital passwords and personal ID documents can no longer meet people's needs. At present, biometric identification systems based on fingerprints and irises have been widely used in financial transactions, computer networks and other applications, which have greatly alleviated the urgent market demand for information security protection. However, these biometric systems still have certain defects, such as being easy to be copied or forged, so it is urgent to find new biometrics to make up for these defect...

AI Technical Summary

Problems solved by technology

[0005] Gu, Y.Y., Zhang, Y.T. used the method of fuzzy decision-making to achieve identity recognition in the article "Photoplethysmographic authentication through fuzzy logic" published at the "IEEE EMBS Asian-Pacific Conference on Biomedical Engineering" in 2003. In the same experimental environment, it can reach 94% Recognition rate, if the environment of the human body is different, due to the influence of breathing, motion artifacts, etc., the recognition rate can only reach 82.3%, which cannot meet the occasions with high requirements for identification

[0006] A.Resit Kavsaoglu, Kemal Polatb and others from Turkey published the article "A novel feature ranking algorithm forbiometric recognition with PPG signals" in the journal "Computers inbiology and medicine" in 2014, using the K nearest neighbor classifier to complete the PPG signal-based Identity recognition, the highest recognition rate is only 94.44%, and the feature dimension of the input classifier is large, and the algorithm complexity is high

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