Signal Segmentation Using Maximum a Posteriori Probability Estimator with Application in Artifact ”corrected” EEG Data
Theodor Dan Popescu · International Journal of Circuits Systems and Signal Processing · 2021
The ”corrected” EEG data, after artifact removing, may be the subject of further investigations, for example segmentation, result- ing new information to be used for feature ex- traction, of great help for medical diagnosis. The paper has as object a generally approach for seg- mentation, making use of Maximum A posteriori Probability (MAP) estimator. The proposed pro- cedure has been used in the analysis of a sample lowpass EEG signals recorded with 13 scalp and 1 EOG electrodes, event-related potential (ERP) data.