Electrocerebral time-frequency component dual positioning normal form quick character input method

Abstract

The invention discloses an electrocerebral time-frequency component dual positioning normal form quick character input method, which includes the steps: (1) exerting visual stimulation on a time domain and a frequency domain after a character input phase is started; (2) dividing channels of EEG (electroencephalogram) signals acquired in real time into two groups according to time-frequency components including SSVEP (steady-state visual evoked potentials) and P300 so as to perform signal processing respectively while a user pays attention to a target character; (3) judging whether the user executes character input operation or not, determining the target character by means of the step (2) and displaying the target character on a character input result display area if the user is judged to execute character input operation, and if the user is judged not to execute character input operation, shifting to a character input interface rather than performing character input, and then shifting to the step (1) so that the user reselects the target character. The method has the advantages of simplicity in principle, convenience in operation, capabilities of improving target identification accuracy rate and increasing character input speed and the like.

Description

technical field [0001] The invention mainly relates to the technical field of brain-computer interface, in particular to a fast character input system designed by adopting dual positioning paradigms of EEG time-domain components and frequency-domain components. Background technique [0002] Brain-Computer Interface (BCI) is a new communication system that does not depend on the participation of peripheral nerves and muscles. It recognizes people's intentions by detecting and distinguishing the spatiotemporal patterns of different brain activities in EEG signals, so as to realize the communication and control between the human brain and the outside world. BCI does not require the participation of human body activities or language expressions, and is non-action and non-contact. The original intention of its research is to serve patients with motor neurological diseases. At present, BCI has broad application prospects in the fields of disability assistance, rehabilitation engi...

AI Technical Summary

Problems solved by technology

So far, although character input has reached a relatively high level by means of detecting P300 and SSVEP respectively, fundamentally speaking, the character input speed of these two paradigms has reached a bottleneck, and it is difficult to achieve further improvement. Significantly improved potential

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