A Brain-Computer Interface Paradigm and Implementation Method for Somatosensory Stimulation Combining Space and Frequency

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 the invention adopts an experimental paradigm combining frequency and space information, and the stimulation method is alternately performed by left and right hands. The experimental paradigm uses only two stimulators to distinguish target stimuli and interference stimuli by frequency, different target stimuli by space, and one experimental sequence only stimulates one target site, the ratio of target stimulus to interference stimuli is 1:5, and the experimental tasks are more complex. For the sake of simplicity, there is no need to superimpose and average the signals, and only one stimulus signal can be used to achieve high classification accuracy, which is more suitable for patients with locked-in syndrome and the elderly. Using the BCI algorithm model based on the secondary CSP to process the EEG signal data, the accuracy of the classification result is higher, and the corresponding control signal is more reliable when applied.

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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