Analysis of sleep staging by Time-Window complexity sequence of EEG
WU Xiao-pei · Journal of Anhui University · 2002
In this paper an approach of time-window complexity sequence is applied to sleep EEG analysis. This method can reduce the loss of state information due to the nonstationarity of EEG signals and the unevenness of state space, and overcome certain limitations of complexity itself in some extent. It will help to extract the state features of EEG in different sleep stages. In addition, we preprocess EEG by adopting ICA and wavelet transform (WT). The results show that some physiological artifacts in EEG can be eliminated effectively by these methods, and sleep staging based on sleep EEG data will therefore become more exact.