Electroencephalogram artifacts removal and rhythm extraction based on state space model
Bin Li · Hebei Journal of Industrial Science and Technology · 2013
State space model is applied to remove artifacts and extract rhythms from electroencephalogram(EEG) time series.Autoregressive moving average model constructed from EEG is manipulated into a compartment model of the state space.With the state variables estimated recurrently by Kalman filter,artifacts are removed and the rhythm components are extracted.The approach is illustrated by means of two application examples of one dimension and multi-dimension EEG during eye-close resting conditions,and the comparison between the latter example and independent component analysis are made.The results indicate that the two examples successfully realize the blink artifacts,power line interference and alpha rhythm extraction,which are associated with eigenvalues of the state transition matrix.The method used in this paper obtains more components than the independent component analysis.