Method and device for removing motion artifacts in EEG signals based on EEMD-PCA

The invention relates to the field of EEG (electroencephalogram) mobile electroencephalogram processing, in particular to a method and a device for removing motion artifacts in EEG signals based on EEMD-PCA (ensemble empirical mode decomposition-principal component analysis). The method and the device comprise the following steps: decomposing single-channel EEG signals based on EEMD to obtain an intrinsic mode function of each order; separating a principal component from the intrinsic mode function of each order based on PCA (Principal Component Analysis); calculating the autocorrelation of each principal component; judging the principal component of which the autocorrelation is greater than a preset threshold value as an artifact principal component; removing the principal components which are judged to be artifacts; carrying out PCA inverse change processing on the remaining principal components, then carrying out EEMD inverse change processing, and obtaining EEG signals with noise removed. Compared with th