Method for brain-computer interface based on amplitude modulated visual evoked potential

Abstract

The invention discloses a method for a brain-computer interface based on amplitude modulated visual evoked potential. The method comprises the following steps of: firstly, connecting an electroencephalogram signal acquisition system; optimally selecting the most-sensitive frequency of amplitude frequency response of a tested person as carrier frequency; maximizing a signal-noise ratio of a response signal; secondly, providing a selection range of modulation wave frequency, designing an AMVEP (Amplitude Modulated Visual Evoked Potential) normal form and generating a stimulation sequence of an amplitude modulated visual evoked potential brain-computer interface normal form; and finally, realizing the identification of single signal or a small amount of signals of the normal form AMVEP. The invention provides the normal form based on the amplitude modulated visual evoked potential and a method for analysis and characteristic extraction of a modulation signal corresponding to the normal form AMVEP. The identification of single signal or a small amount of signals of the normal form AMVEP based on the amplitude modulated visual evoked potential is realized; and the method disclosed by the invention has the advantages of simpleness in operation, fewer electrodes and more target numbers.

Description

technical field [0001] The invention relates to the technical field of brain-computer interface, in particular to a brain-computer interface method based on amplitude modulation of visual evoked potential. Background technique [0002] The brain-computer interface is a system that realizes direct communication and control between the brain and computers or other electronic devices based on EEG signals. Brain-Computer Interface (BCI for short), as a kind of Human-computer interface (HCI for short), can directly convert the information sent by the brain into commands that can drive external devices, and replace human Muscle tissues such as limbs realize the communication between human and the outside world and the control of the external environment. Since it does not rely on the conventional brain output pathway, it opens up a new way for the human brain to communicate and control information with the outside world, making the use of human brain signals The idea of ​​direct ...

AI Technical Summary

Problems solved by technology

[0004] In the current SSVEP-BCI system application, SSVEP mainly uses the low-frequency region below 30Hz, and adopts a cursor flickering stimulation method in which a frequency represents a target task. Due to the limitation of the frequency region, frequency resolution and response amplitude of the target performance, in order to Guarantee the recognition accuracy of target tasks, so that the number of task targets that can be presented is limited

At the same time, the traditional SSVEP identification efficiency is low, requiring the accumulation of multiple stimulation signals, which seriously affects the real-time identification ability

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