Steady state evoked potential brain-computer interface method based on reciprocating swing visual perception

Abstract

The invention discloses a steady state evoked potential brain-computer interface method based on reciprocating swing visual perception. Sector reciprocating swing is realized by using the sensitivity of human eyes to swinging motion perception and adopting red sector reciprocating swing as a normal form in a constant angular velocity mode. A brain electrical signal generated in a way that a user watches a stimulating pattern is acquired by brain electrical acquiring equipment, and is subjected to amplifying, filtering and A/D (Analog/Digital) conversion, and then the processed brain electrical signal is inputted into a computer; feature extraction and classification and identification of the acquired brain electrical signal are realized by using canonical correlation analysis. According to the steady state evoked potential brain-computer interface method disclosed by the invention, visual information of color, shape, motion and the like is fused; in addition, a normal form area is smaller, and stimulation received by the human eyes is less, so that visual fatigue of the user is reduced, a signal-noise ratio of EEG (Electroencephalograph) is improved, and stimulating frequency can be induced at a middle-frequency band. The steady state evoked potential brain-computer interface method has higher recognition accuracy for a watched object, and has the characteristics of low flicking and low applicability; interaction performance of a brain-computer interface can be improved.

Description

technical field [0001] The invention relates to the technical field of brain-computer interface, in particular to a steady-state visual evoked potential brain-computer interface method based on swing visual perception. Background technique [0002] Brain-computer interface (BCI) commonly used methods include motor imagery, P300 event-related potential, transient visual evoked potential, steady-state visual evoked potential (SSVEP) and so on. In comparison, the steady-state visual evoked potential requires fewer electrodes, the user does not need training, and the recognition accuracy is higher. However, brain-computer interfaces based on SSVEP often use stimulation methods such as light flickering or graphic flipping, which can easily cause visual fatigue of users and reduce the accuracy of recognition, which limits its further application. In recent years, some scholars have proposed a brain-computer interface method based on motion perception, which can avoid the negative...

AI Technical Summary

Problems solved by technology

However, the pattern in the central area of ​​the Newton ring destroys the property that the Newton ring maintains a constant brightness during the movement, reduces the spectral peak signal-to-noise ratio, and is not conducive to reducing the visual fatigue of the user.

In order to keep the brightness constan

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