A Feature Extraction Method Using ECG Signals for Automatic Identity Recognition

Abstract

The invention discloses a feature extraction method for automatic identity recognition by using electrocardiographic signals. The noise of the electrical signal, search the second-order differential zero point of the training set ECG signal, detect the R wave of the training set ECG signal, and divide it into a training set pseudo-heart beat signal matrix; (2) extract the training set heart rate by using the training set pseudo-heart beat signal matrix The characteristics of the electrical signal: calculate the power spectral density matrix and autocorrelation matrix of the pseudo-cardiac signal matrix of the training set, and integrate the transformation domain features of the training set and the time domain features of the training set; (3) convert the ECG signal to be identified into Pseudo-heartbeat signal; (4) using the pseudo-heartbeat signal to be identified to extract features of the electrocardiogram signal to be identified. The invention effectively reduces the signal acquisition time required for identity identification, improves identification accuracy and reduces calculation cost.

Description

technical field [0001] The invention relates to the technical field of identification, in particular to a feature extraction method for automatic identification using electrocardiographic signals. Background technique [0002] The electrocardiogram is unique to an individual and can be used as an important basis for human identification. The identification device based on the electrocardiographic signal refers to a device that can automatically identify the identity of the person who receives the electrocardiographic signal from outside. [0003] The definition of using ECG signal for identity recognition is: given an ECG signal, determine the identity of the person to whom the signal belongs. A system or device for automatic identification using ECG signals is usually implemented based on the pattern recognition technology of ECG signals, and two necessary links, feature extraction and recognition of ECG signals, need to be realized. Among them, the feature setting in the...

AI Technical Summary

Problems solved by technology

[0004] In the disclosed inventions of devices and methods for identification using ECG signals, features are often extracted through a relatively long period of ECG signals, and there are two problems. On the one hand, users need to wait for a long time to perform ECG signals On the other hand, a larger amount of data requires more computing costs

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