Electroencephalogram identification method based on different expression drivers

Abstract

The present invention discloses an electroencephalogram identification method based on different expression drivers, which is characterized in that based on cerebrophysiology knowledge, firstly, electroencephalograms generated by different face expression drivers are subjected to modeling simulation analysis; and on the basis, signal features of an Alpha wave band and a theta wave band in the electroencephalograms, which are generated on the basis of positions of four measurement points of FC5, FC6, F7 and F8 of the brain in the face expression driving process, are used as the basis of electroencephalogram classification identification for driving control of the electroencephalograms.

Description

technical field [0001] The invention relates to brain-computer interface technology, in particular to a method for researching brain electrical signals driven by facial expressions. Background technique [0002] The latest development of brain-computer interface technology has developed from a simple brain-computer interface to a brain-electromechanical device, that is, by extracting the EEG signals generated by the human brain cortex, inferring the thinking activities of the brain and translating them into corresponding commands to control peripheral electromechanical devices, such as disabled wheelchairs, smart prosthetic hands or exoskeleton robots, etc., in order to realize the mind control of these peripheral devices. With the development of biomechatronics technology in recent years, more and more characteristic EEG signals have been applied in the research of brain-computer interface paradigm. According to different control sources, BCI systems are mainly divided int...

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Problems solved by technology

Although the evoked EEG signal has the characteristics of high resolution and strong anti-interference ability, its disadvantage is that it relies too much on the inducing source, and at the same time, it is easy to cause fatigue and even induce epilepsy after a long time inducing experiment.

Tsinghua University realized the pouring process of the four-free prosthesis through the steady-state visually induced brain-computer interface system, but the long-term light intensity stimulation will reduce the accuracy of the experiment

[0004] At present, domestic scholars still mainly focus on the research of motor imagery, motion recognition, and steady-state visually evoked brain-computer interface systems. However, research on EEG signals driven by facial expressions has not yet seen mature technical reports on related topics.

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