Implementation method and device of brain-computer interface system based on dynamic ssvep paradigm

Abstract

The invention discloses a method and device for implementing a brain-computer interface system based on a dynamic SSVEP paradigm. The implementation method includes: acquiring a real-time picture to obtain environmental information to be identified; constructing and training an object tracking model, and inputting the environmental information into the object tracking model, Obtain the real-time position information of the object in the environmental information; according to the position information of the object, use SSVEP scintillation blocks of different frequencies to mark different objects in the screen respectively, and update the coordinates of the SSVEP scintillation block according to the real-time position information of the object to obtain The picture superimposed with SSVEP information is presented to the test subject, and the EEG signal sequence of the test subject is collected; the FBCCA method is used to analyze the EEG signal sequence, and the object that the test subject is looking at is obtained according to the analysis result. The invention can effectively solve the problems that the traditional SSVEP paradigm control is not intuitive and the user's sense of interaction is not high, and the accuracy of brain-computer signal classification is improved.

Description

technical field [0001] The present invention relates to the technical field of brain-computer interface, in particular to a method and device for implementing a brain-computer interface system based on the dynamic SSVEP paradigm. Background technique [0002] Brain-Computer Interface (BCI) can automatically identify people's intentions, and use the signals of the brain to control external devices without relying on the nervous system and muscles, so as to communicate and interact with the outside world. This technology is widely used in post-operative rehabilitation training, nursing care of critically ill and disabled people, intelligent prosthetics and mechanical equipment control. Compared with other methods, SSVEP (Steady State Visual Evoked Potential, Steady State Visual Evoked Potential) needs to record fewer EEG data channels, does not require training, and can achieve higher recognition. However, current research usually uses different frequencies of flicker output ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a method and device for implementing a brain-computer interface system based on the dynamic SSVEP paradigm, so as to solve the technical problems existing in the prior art, and can effectively solve the problems that the traditional SSVEP paradigm control is not intuitive and the user interaction is not high. , improving the accuracy of brain-computer signal classification

Images