EEG Channel Selection Method Based on Feature Fusion
In order to predict epilepsy more accurately,an algorithm of EEG channel selection based on feature fusion is proposed.The sample entropy,permutation entropy,and variance features are fused based on the position of electroencephalogram electrodes,and the fused features are used as inputs for the electroencephalogram channel selection algorithm for epilepsy prediction.The results show that the fused features achieved an accuracy of 96.74％and a fitness function value of 0.93 when using 9 electroencephalogram channels,which is much higher than other feature combinations.
NETL
NSTL
万方数据
