Brain-computer interface system implementation method and device based on dynamic SSVEP normal form

Abstract

The invention discloses a brain-computer interface system implementation method and device based on a dynamic SSVEP normal form, and the method comprises the steps: obtaining a real-time image, and obtaining to-be-recognized environment information; constructing and training an object tracking model, and inputting the environment information into the object tracking model to obtain real-time position information of the object in the environment information; according to the position information of an object, adopting SSVEP scintillation blocks with different frequencies to mark different objects in the picture respectively, updating coordinates of the SSVEP scintillation blocks according to real-time position information of the objects, obtaining and presenting the picture overlaid with SSVEP information to a to-be-tested person, and collecting an electroencephalogram signal sequence of the to-be-tested person; and analyzing the electroencephalogram signal sequence by adopting an FBCCAmethod, and obtaining an object watched by the to-be-tested person according to an analysis result. According to the method, the problems that traditional SSVEP normal form control is not visual andthe user interaction feeling is not high can be effectively solved, 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 realizing a brain-computer interface system based on a dynamic SSVEP paradigm. Background technique [0002] Brain-Computer Interface (BCI) can automatically recognize people's intentions, using the signals of the brain, without relying on the nervous system and muscles to control external devices, and then communicate and interact with the outside world. This technology is widely used in postoperative rehabilitation training, nursing care of the critically ill and disabled, 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, requires no training, and can obtain a higher degree of recognition. However, the current research usually uses different frequency flashes at differe...

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