Electrocardiosignal data processing method

Abstract

The invention discloses an electrocardiosignal data processing method. The electrocardiosignal data processing method comprises the following steps of (1) collecting data of electrocardiosignals; (2) carrying out preprocessing on the collected data of the electrocardiosignals, wherein baseline drift removal processing and de-noising processing are carried out on the collected electrocardiosignals; (3) decomposing the electrocardiosignals into single-cycle electrocardiosignal sets; (4) carrying out characteristic extraction, carrying out signal classification according to single-cycle electrocardiosignals after normalization and the level of similarity of curve signals, and choosing electrocardiosignals in the maximum class as a template; (5) detecting signal input, carrying out similarity comparison between the electrocardiosignals and a central database template to determine the identity. According to the single-leading electrocardiosignal data processing method, the mode of characteristic curve matching is adopted to carry out curve similarity comparative studies on electrocardiosignal sequences, and complex procedures for extracting characteristic points are avoided.

Description

【Technical field】 [0001] The invention relates to an identity identification technology, in particular to a method for using electrocardiographic signals to process data and then identify an identity. 【Background technique】 [0002] With the development of computer network and electronic technology, a new identity verification method has emerged to replace traditional passwords and passwords - biometric identification technology. Biometric identification technology refers to a technology that uses human biological characteristics or behavioral characteristics for identity authentication. [0003] Automatic identification systems based on biometric features have roughly the same working principle and working process. The first is to collect samples, which can be fingerprints, face images, etc.; the second is to perform feature extraction. According to the unique and unique features of the samples, an algorithm is used to assign a feature code to it, and the feature code is s...

AI Technical Summary

Problems solved by technology

However, the existing identification technology based on ECG signals uses multiple feature points in each lead of 12-lead ECG signals as unique and characteristic identification feature information. This identification technology needs to collect 12-lead ECG signal, signal acquisition is relatively cumbersome, only suitable for professionally trained hospital doctors, it is difficult to apply to family and personal medical monitoring

At the same time, since the collected feature information is discrete data, the calculation is complicated and the accuracy of the distinction is not high

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