Brain-Computer Interface Using Brain Power Map and Cognition Detection Network During Flight

Abstract

This article presents a new aviation brain-computer interface, which includes the construction of a color brain power map and a cognitive detection network. The developed network, Bpmnet, can effectively detect the cognitive state of the brain. To improve the effectiveness of model parameter optimization algorithms, momentum and batch normalization are proposed during Bayesian posterior parameter inference. Bpmnet reduces the risk of model overfitting and increases the uncertainty of outlier prediction. Experimental results demonstrate that our approach significantly outperforms state-of-the-art techniques.