Electrocardiogram identity authentication method based on wearable equipment

Abstract

The invention discloses an electrocardiogram identity authentication method based on wearable equipment. According to the method, an electrocardiogram input by a user is subjected to preprocessing, feature point detection and feature extraction, and extracted electrocardiogram features are matched and compared with a feature template in a user database. Aiming at the electrocardiogram noise reduction problem on the wearable equipment, the mixed three-layer noise reduction is designed, noise signals can be effectively removed, the mixed three-layer noise reduction combines the advantages of morphological filtering and frequency domain filtering, the implementation method is simple and convenient, and the signal quality of an electrocardiogram obtained after filtering can be remarkably guaranteed. The user characteristic template constructed by the invention reserves respective hard index and soft index characteristics of the reference characteristic and the non-reference characteristicof the electrocardiogram, so that the authentication accuracy of the system is ensured.

Description

technical field [0001] The invention belongs to the field of biological authentication, in particular to an electrocardiogram identity authentication method based on a wearable device. Background technique [0002] In recent years, wearable devices (such as smart watches) have been widely used in mobile payment, mobile communication, health information monitoring, smart home interaction and other fields. There are smart watches with ECG measurement function, such as Apple Watch and Huami Technology's health watch. [0003] In the past, the research data in electrocardiogram research were all collected by electrocardiographs with high anti-interference and high precision. This kind of electrocardiogram data has a high signal-to-noise ratio, and there is no high-energy low-frequency noise and high-frequency noise. Therefore, the previous research on ECG recognition and authentication can remove the noise in ECG with only one pass band-pass filtering. However, this frequency-...

AI Technical Summary

Problems solved by technology

However, this frequency-domain filtering method is not suitable for removing noise in ECG collected by wearable devices

The signal-to-noise ratio of the ECG collected by wearable devices is low, and the high-energy noise frequency band covers the key low-frequency area of ​​the ECG. Frequency domain filtering cannot effectively extract the frequency band representing the ECG signal from the frequency band where the signal and noise are mixed.

On the other hand, when constructing user feature templates, previous studies often ignore the characteristics of ECG features and directly construct feature templates. Few studies distinguish these two types of features, let alone adjust the two types of features in the user feature template. proportion, the feature template constructed in this way cannot fully represent the user's ECG information

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