Evaluation of chaotic EEG signals in pilots based on Bayesian networks
The discrete dynamic system composed of facial evoked EEG signal and basis function iteration is cha-otic,which leads to the poor evaluation effect of pilot fatigue assessment for EEG signal at present.In this regard,the pilot fatigue assessment method under chaotic EEG signals is studied.Firstly,the pilot EEG signals are de-chaotized by using the empirical mode decomposition method.Then,the pilot EEG feature vectors are extracted by the bagging regularized spatial pattern method.Finally,the pilot EEG signal feature vector is input into the hidden Markov model(HMM)and Bayesian network combination model to complete the pilot fatigue assessment.The experimental results show that the accuracy of the pilot fatigue assessment of the proposed method is 91.7%,and the pilot fatigue error is 1%～4%.More accurate pilot fatigue assessment results are obtained.
万方数据
维普
