A brain-computer interface system and implementation method based on auditory attention and multifocal electrophysiology

Abstract

The present invention relates to a brain-computer interface system and implementation method based on auditory attention and multi-focal electrophysiology. The amplifier module can simultaneously generate sound sources with multiple frequencies and multiple channels, and distribute them in different positions in the virtual auditory space; each sound source is controlled by the same M sequence, and when the M sequence is 1, the sound source emits sound, and it is 0 No sound from time to time; the signal acquisition module acquires the mixed electrophysiological signal of the auditory response through the sensor, and performs signal amplification and analog / digital conversion; the signal processing module performs fast cross-correlation calculation on the mixed electrophysiological signal and the M sequence to obtain each sound source Corresponding auditory response signals; then extract the eigenvalues ​​of the auditory response signals of each sound source, classify the feature vectors through the discriminant classification module, and decode the sound sources noticed by the subject's auditory sense, so as to determine what the subject thinks , and then control the execution module to execute corresponding actions.

Description

Technical field: [0001] The invention discloses a brain-computer interface system and a realization method based on auditory attention and multi-focal electrophysiology, and belongs to the intersecting technical field of neurocognitive science, information processing, and automatic control. Background technique: [0002] Brain-computer interface is one of the hot topics in neuroengineering research. Brain-computer is to establish a direct communication and control channel between the human brain and computers or other electronic devices. Through this channel, people can express ideas or operate devices directly through the brain, without the need for language or physical actions. [0003] For those patients who have completely lost peripheral neuromuscular control, if they want to control the external environment, such as controlling the surrounding electrical equipment, they must interpret brain signals into corresponding control commands. There are many ways to generate ...

AI Technical Summary

Problems solved by technology

However, in this method, it is difficult to decode the information contained in the signal, and the individual differences are also large.

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