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

Abstract

The invention discloses a high-performance motor imagery online brain-computer interface system based on OpenVIBE. The system comprises a signal collection device, a signal testing script, a signal collection script, a data training script and an online experiment script, wherein the signal testing script is connected with the signal collection device, and the signal quality is detected through the signal testing script; an experiment parameter is set through the signal collection script, and motor imagery experimental data is collected; a time-space filtering classifier is trained by using the data training script based on RSTFC algorithm, and the specific time-space filtering classifier is introduced into the online experiment script; and the high-performance motor imagery online brain-computer interface system is realized by the online experiment script according to the time-space filtering classifier obtained in training. The readability and flexibility of the system can be improved by adopting a modularized designing method, function extension can be facilitated, and the working efficiency of researchers can be greatly improved. The high-performance motor imagery online brain-computer interface system 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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