科技创新与应用2024，Vol.14Issue(36)：47-50,4.DOI:10.19981/j.CN23-1581/G3.2024.36.010
基于压缩感知的疲劳驾驶脑电信号监测方法
摘要
Abstract
Electroencephalogram(EEG)signals can be used to effectively determine whether the driver is tired or not.In order to reduce the amount of brain electrical signals collected by the driver during driving,the driver's brain electrical signals are sparse using discrete cosine bases at the signal sampling end,and then the sparse high-dimensional signals are compressed and sampled into low-dimensional signals through Bernoulli matrix.Finally,the compressed and sampled low-dimensional signals are reconstructed on the computer side of the vehicle using the base tracking noise reduction method to restore the original EEG signals.Experiments on simulated driving and compression sampling of EEG signals were conducted in the laboratory.The results showed that when the compression ratio was less than 80%,the error of the reconstructed EEG signal was less than 0.26.The method can ensure the accuracy required by the fatigue monitoring system.关键词
脑电信号/疲劳驾驶/压缩采样/压缩感知/监测方法Key words
electroencephalogram(EEG)signal/fatigue driving/compressed sampling/compressed sensing/monitoring methods分类
交通工程引用本文复制引用
辛增念,刘艳杰..基于压缩感知的疲劳驾驶脑电信号监测方法[J].科技创新与应用,2024,14(36):47-50,4.基金项目
江西省教育厅科学技术重点研究项目(GJJ212003) （GJJ212003）
江西科技学院协同创新中心开放基金重点项目(XTCX2104) （XTCX2104）
