Title :
Independent Component Analysis and Time-Frequency Method for Noisy EEG Signal Analysis
Author :
Ye, Ning ; Wang, Xu ; Sun, Yuge
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang
Abstract :
EEG signal recorded by scalp electrode is a mixture of signals from different brain regions and with noisy signal. Independent component analysis (ICA) is essentially a method for extracting individual signals from mixtures of signals. Time-frequency analysis provides a powerful tool for the analysis of EEG signals. The original EEG signal is divided into independent components, and the noisy components were chosen by time-frequency analysis method. The results show that reconstructed the reserved components can obtain clean EEG signal
Keywords :
biomedical electrodes; electroencephalography; independent component analysis; medical signal processing; time-frequency analysis; ICA; brain regions; independent component analysis; noisy EEG signal analysis; scalp electrode; time-frequency method; Acoustic noise; Electrodes; Electroencephalography; Entropy; Independent component analysis; Scalp; Signal analysis; Signal processing; Sun; Time frequency analysis;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345938