Somatosensory stimulation brain-computer interface paradigm combining space and frequency and implementation method

Abstract

The invention discloses a somatosensory stimulation brain-computer interface paradigm combining space and frequency and an implementation method, the brain-computer interface paradigm designed by theinvention adopts an experimental paradigm combining frequency and space information, and the stimulation mode is left-hand and right-hand alternation. Only two stimulators are used, target stimulationand interference stimulation are distinguished by frequency, different target stimulation is distinguished by space, only one target part is stimulated by one experimental sequence, the ratio of thetarget stimulation to the interference stimulation is 1: 5, experimental tasks are simpler, signals do not need to be superposed and averaged, and experimental efficiency is improved. High classification precision can be achieved by using only one stimulated signal, and the method is more suitable for patients with atresia syndrome and the like and old people. The BCI algorithm model based on thesecondary CSP is adopted to process the electroencephalogram signal data, the precision of the classification result is higher, and the corresponding control signal is more reliable when the method isapplied.

Description

technical field [0001] The present invention relates to a brain-computer interface (BCI) paradigm, in particular to a somatosensory stimulation brain-computer interface paradigm and an implementation method combining space and frequency. Background technique [0002] Many diseases such as stroke, cerebral palsy, locked-in syndrome, etc. will damage the neural pathways that the brain communicates and controls with the external environment, and severe patients even completely lose the ability to communicate with the outside world. These patients cannot normally communicate with the outside world through the brain output pathway, and these problems seriously affect the survival ability and quality of life of the elderly. The brain-computer interface technology does not rely on the peripheral neuromuscular pathways of the human body, and directly communicates with the external environment through the brain. Therefore, for patients with healthy brain thinking but damaged neural ...

AI Technical Summary

Problems solved by technology

The average accuracy of 3 healthy users reached 86.7%, but it takes 12 times to stack and average, and it takes 38s to output a command

However, the existing paradigms are mostly complex multi-classification, which is difficult to implement, and often requires a certain amount of training to achieve better classification accuracy.

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