Network environment-oriented electroencephalogram identification system and network environment-oriented electroencephalogram identification method

Abstract

The invention relates to a network environment-oriented electroencephalogram identification system and a network environment-oriented electroencephalogram identification method. The identification system comprises a plurality of wearable electroencephalogram measuring devices, more than one mobile network terminal and an electroencephalogram data processing device; the electroencephalogram measuring devices are used for processing measured electroencephalograms into network electroencephalogram data and transmitting the network electroencephalogram data to the electroencephalogram data processing device for processing; the electroencephalogram data processing device is used for outputting an identification result and transmitting the identification result to a mobile network terminal for displaying. The identification method comprises the steps of measuring the electroencephalograms of a tested individual by using the electroencephalogram measuring devices and processing the electroencephalograms into the network electroencephalogram data, transmitting the electroencephalogram data to the electroencephalogram data processing device by virtue of a wireless network card of the mobile network terminal, performing segment treatment on the electroencephalograms and extracting electroencephalogram characteristic information by use of the electroencephalogram data processing device, screening electroencephalogram characteristic vector training samples based on reputation computing, and determining the input sample and the degree of membership of a fuzzy support vector machine, thereby completing the identification of the tested individual and outputting the result.

Description

technical field [0001] The invention relates to an identity recognition system and a recognition method, in particular to a network environment-oriented EEG signal recognition system and a recognition method. Background technique [0002] The process of social informatization and networking has put forward new requirements for identification technology. In recent years, many attacks on network identity databases have seriously affected the privacy of users, the rights and interests of enterprises and even the stability of society. Therefore, the new identification technology must not only meet the basic requirements of safety and reliability, but also need to adapt to the network environment. At present, common identification technologies can be divided into three categories: identification technologies based on specific knowledge such as passwords and passwords, identification technologies based on specific possessions such as ID cards and passports, and identification tec...

AI Technical Summary

Problems solved by technology

However, due to the small amount of sparse EEG data, the characteristics of being easily affected by external noise, the unstable data transmission environment of the network, and the sensitivity of the support vector machine itself to the noise of the input training samples, the traditional support vector machine method cannot Adapt to the needs of EEG data classification in the network environment

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