EEG Fatigue Detection Based on Common Spatial Pattern
Because EEG can directly reflect the fatigue state of cerebral cortex,this paper proposes a fatigue detection method based on common spatial pattern.Firstly,the data set is preprocessed by filtering,and then the common spatial pattern is used to ex-tract features.Finally,the effective spatial features are classified by support vector machine.In addition,the experiment also uses 5 fold and 10 fold cross validation method to evaluate the method.It explores the value of correlation coefficient m of EEG fatigue char-acteristic order,divides the brain regions and compares the accuracy of fatigue recognition in each region.The results show that,the recognition rate of this method is higher than that of the methods based on sample entropy and fuzzy entropy,the average fatigue de-tection accuracy rate can reach 98.54%,the whole scalp fatigue recognition rate is the highest,and the frontal fatigue recognition rate is better than other regions,up to 92.54%.This study can provide a more simple and accurate detection method for the develop-ment of fatigue detection equipment,and help to promote the application of wearable brain computer interface in fatigue driving ear-ly warning.
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