Title :
EEG Ocular Artefacts and Noise Removal
Author :
Romo-Vazquez, R. ; Ranta, R. ; Louis-Dorr, Valerie ; Maquin, Didier
Abstract :
The general framework of this research is the pre-processing of the electroencephalographic (EEG) signals. The goal of this paper is to compare several combinations of wavelet denoising (WD) and independent component analysis (ICA) algorithms for noise and artefacts removal. These methods are tested on simulated EEG, using different evaluation criteria. According to our results, the most effective method consists in source separation by SOBI-RO [1], followed by wavelet denoising by SURE thresholding [2].
Keywords :
electroencephalography; independent component analysis; medical signal processing; signal denoising; EEG ocular artefacts; SURE thresholding; artefact removal; electroencephalographic signals; independent component analysis; noise removal; signal preprocessing; wavelet denoising; Additive noise; Brain modeling; Electroencephalography; Independent component analysis; Noise reduction; Signal processing; Signal processing algorithms; Signal to noise ratio; Source separation; Testing; Aged; Algorithms; Artifacts; Diagnosis, Computer-Assisted; Electroencephalography; Epilepsy; Eye Movements; Female; Humans; Male; Principal Component Analysis; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4353577
