Open AccessAn early warning method for structural safety based on EEG
Author(s) -
Jailong Li,
Wei Zheng,
Zhao Quan
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1325/1/012091
Subject(s) - electroencephalography , signal (programming language) , computer science , artificial intelligence , warning system , power (physics) , pattern recognition (psychology) , computer vision , speech recognition , psychology , physics , neuroscience , telecommunications , quantum mechanics , programming language
It is an important part in the field of structural safety detection to warn the monitored results accordingly. Studying the effect of visual environment on EEG can provide theoretical evidence for structural security warning. Most of the existing studies on the effect of visual environment on EEG are based on a single factor of color or frequency, and seldom involve the effect of shape on EEG. In order to solve these problems, this paper carried out an experiment to explore the effect of color, frequency and shape on EEG. The EEG signal was pretreated by EMD-HHT algorithm. It was found that the effects of visual signals on brain waves were concentrated in the first 20 seconds. By the observed β power in the first 20 seconds we found that when the color is red or yellow, the frequency is 10 Hz, the shape is circular or triangular, the β power will increase significantly, it’s the electroencephalogram most relevant to attention.