论文信息 - Ocular Artifact Suppression in Multichannel EEG Using Dynamic Segmentation and Enhanced wICA - 字舞流文

Ocular Artifact Suppression in Multichannel EEG Using Dynamic Segmentation and Enhanced wICA

The artifacts such as ocular, muscle and certain electrical disturbances contaminate the Electroencephalogram (EEG). Wavelet enhanced independent component analysis (wICA) with static segmentation ...

K. P. Paradeshi | U. D. Kolekar | U. Kolekar

[1] T. Lagerlund,et al. Spatial filtering of multichannel electroencephalographic recordings through principal component analysis by singular value decomposition. , 1997, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[2] Anestis Antoniadis,et al. Wavelet methods in statistics: Some recent developments and their applications , 2007, 0712.0283.

[3] Bashir I. Morshed,et al. Unsupervised Eye Blink Artifact Denoising of EEG Data with Modified Multiscale Sample Entropy, Kurtosis, and Wavelet-ICA , 2015, IEEE Journal of Biomedical and Health Informatics.

[4] Atilla Kilicarslan,et al. A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements , 2016, Journal of neural engineering.

[5] I. Johnstone,et al. Minimax estimation via wavelet shrinkage , 1998 .

[6] T. Sejnowski,et al. Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects , 2000, Clinical Neurophysiology.

[7] Christian Jutten,et al. On the blind source separation of human electroencephalogram by approximate joint diagonalization of second order statistics , 2008, Clinical Neurophysiology.

[8] V. A. Makarov,et al. Recovering EEG brain signals: Artifact suppression with wavelet enhanced independent component analysis , 2006, Journal of Neuroscience Methods.

[9] I. Johnstone,et al. Ideal spatial adaptation by wavelet shrinkage , 1994 .