High-performance motor imagery online brain-computer interface system based on openvibe

Abstract

The invention discloses an OpenVIBE-based high-performance motor imagery online brain-computer interface system, including signal acquisition equipment, signal test scripts, signal acquisition scripts, data training scripts and online experiment scripts, wherein the signal test script is connected to the signal acquisition equipment, Detect the signal quality through the signal test script, then set the experimental parameters through the signal acquisition script and collect the data of the motor imagery experiment, then use the data training script to realize the training of the spatio-temporal filter classifier based on the RSTFC algorithm, and obtain the specific spatio-temporal filter classifier to import The online experiment script is described, and the online experiment script implements a high-performance online brain-computer interface system for motor imagery based on the trained spatio-temporal filter classifier. The invention adopts a modular design method to improve the readability and flexibility of the system, is convenient for function expansion, greatly improves the work efficiency of researchers, and has the advantages of high accuracy and good performance.

Description

technical field [0001] The invention relates to the field of online brain-computer interface for motor imagery, in particular to a high-performance online brain-computer interface system for motor imagery based on OpenVIBE. Background technique [0002] Brain-computer interface (BCI) is a technical means to realize the direct interaction between the human brain and external devices, and has achieved great development in the world in recent years. At present, the known brain-computer interface system can be divided into three parts, which are data acquisition, signal processing and device control. Among them, the data acquisition mainly involves the hardware part, mainly including the electrode cap, signal amplifier and power supply, etc., and the potential signal of the cerebral cortex is input to the computer system. Since the strength of the EEG signal is very weak, signal denoising and signal amplification processing are required during the signal acquisition process, bo...

AI Technical Summary

Problems solved by technology

Therefore, the current brain-computer interface research is still mainly in the laboratory stage, and there is still a certain gap with the requirements of practical applications.

[0006] (2) Low degree of online: The field of brain-computer interface has been called an increasingly popular research direction, but these studies mainly focus on offline analysis

[0007] (3) Isolation of experimental research: Different research institutions or units will have their own experimental equipment and corresponding experimental systems, but the degree of correlation between these systems is very low

This creates such a phenomenon: when adding new theoretical results from outside to the original system, it often requires a lot of extra work, so the conversion efficiency between theory and practice is often not high

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