HHT-based high-frequency combined coding steady state visual evoked potential brain-computer interface method

Abstract

The invention discloses a Hilbert-Huang Transform (HHT)-based high-frequency combined coding steady state visual evoked potential brain-computer interface method, which comprises the following steps of: connecting hardware, expressing different targets by using nn stimulation sequences formed by time sequence permutation and combination through n high-frequency stimulation frequencies, coding thestimulation sequences to form a code base, then executing electroencephalogram data characteristics by adopting a Hilbert-Huang Transform (HHT)-based variable frequency electroencephalogram signal characteristic extraction method, acquiring a Hilbert time-frequency graph of the electroencephalogram data, and comparing the extracted electroencephalogram data characteristics with the code base by using a local frequency spectrum extreme value target identification method to realize quantified target identification accuracy. The method has the advantages of simple operation, little electrode number, more target number, reduction of testee fatigue, and reduction of probability of inducing testee epilepsy.

Description

technical field [0001] The invention relates to the technical field of Brain-Computer Interface (Brain-Computer Interface, BCI), in particular to a brain-computer interface method based on HHT high-frequency combination coding steady-state visual evoked potentials. 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), as a kind of human-computer interface (HCI for short), opens up a new way for the human brain to communicate and control information with the outside world because it does not rely on conventional brain output pathways. The approach makes it possible to use human brain signals to directly control external devices. In recent years, brain-computer interface (BCI) technology has developed very rapidly, and has shown important value in fields such as biomedicine, virtual reality, game ente...

AI Technical Summary

Problems solved by technology

[0004] However, at present, the general SSVEP-BCI system routinely adopts the low frequency band of 6-25 Hz, and basically adopts a simple paradigm in which one task is represented by one frequency; however, due to the limitation of frequency resolution and screen refresh rate, within the limited frequency range, it is possible to The number of task targets presented is limited; in addition, in practical applications, the low-frequency flicker stimulation of low-frequency SSVEP is likely to cause visual fatigue to the subjects, and may even induce seizures in the subjects, so the comfort of the system for long-term use cannot be guaranteed sex

Images