Identification method based on EEG phase synchronization

A phase synchronization and identity recognition technology, applied in the field of EEG signal recognition, can solve the problems of easy forgery and loss of identity authentication, and difficulty in meeting the needs of society.

Active Publication Date: 2014-04-30
HANGZHOU DIANZI UNIV
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Problems solved by technology

Traditional identity authentication is easy to be forged and lost, and it is becoming more and more difficu

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  • Identification method based on EEG phase synchronization
  • Identification method based on EEG phase synchronization
  • Identification method based on EEG phase synchronization

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Embodiment Construction

[0055] The present invention will be further described below in conjunction with accompanying drawing.

[0056] Such as figure 1 Shown: First collect the required EEG signal, then perform preprocessing on the EEG data, such as filtering and removing the average reference, and then filter the preprocessed data to a specific frequency band to calculate the phase lock value. The phase synchronization feature of the EEG signal was obtained by calculating the phase-locked value, and after dimensionality reduction by principal component analysis, the feature vector was classified by linear discriminant analysis.

[0057] Refer to attached figure 2 , the specific implementation steps of the present invention are as follows:

[0058] Step S1: Collect the required EEG signals through a multi-channel EEG acquisition device. In this embodiment, a 16-electrode g-tec device is used to obtain EEG data, the sampling frequency is 256Hz, the electrode cap adopts the international 10 / 20 sys...

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Abstract

The invention relates to an identification method based on EEG phase synchronization. According to the method, phase synchronization characteristics of EEG are calculated by a phase locking value mainly, and different individuals are identified by means of linear discriminant analysis. The method includes: data collection, data preprocessing, filtering, phase synchronization characteristic calculation, eigenvector dimensionality reduction, eigenvector classification, and classification accuracy calculation. Classification results show that good classification results are obtained by using EEG phase synchronization as biological identification characteristics and different individuals can be effectively identified. Compared with the traditional biological identification characteristics, the EEG phase synchronization characteristics provide better safety and imperceptibility, and the method is applicable to certain persons with physical disabilities or injuries.

Description

technical field [0001] The invention belongs to the field of electroencephalogram signal identification in the field of biological feature identification, and in particular relates to an identification method for classifying and extracting phase synchronization features based on the phase synchronization of electroencephalogram signals. Background technique [0002] How to accurately identify a person's identity and protect information security is a key social problem that must be solved in today's information age. Traditional identity authentication is very easy to forge and lose, and it is increasingly difficult to meet the needs of society. Biometric identification is currently the most convenient and safe solution. [0003] Biometric identification identifies individuals through their physiological or behavioral characteristics. Since each person's biological characteristics are unique and stable, and not easy to forge, it is more reliable and accurate to use biometric ...

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Application Information

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IPC IPC(8): A61B5/117A61B5/0476G06F19/00
Inventor 孔万增徐思佳周凌霄徐飞鹏任银芝
Owner HANGZHOU DIANZI UNIV
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