EEG Ocular Artefacts and Noise Removal
Copyright policy )EEG Ocular Artefacts and Noise Removal
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].
Male, Principal Component Analysis, Epilepsy, Eye Movements, Reproducibility of Results, Electroencephalography, Signal Processing, Computer-Assisted, Sensitivity and Specificity, Humans, Female, Diagnosis, Computer-Assisted, Artifacts, Algorithms, Aged
Male, Principal Component Analysis, Epilepsy, Eye Movements, Reproducibility of Results, Electroencephalography, Signal Processing, Computer-Assisted, Sensitivity and Specificity, Humans, Female, Diagnosis, Computer-Assisted, Artifacts, Algorithms, Aged
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