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Interictal EEG noise cancellation: GEVD and DSS based approaches versus ICA and DCCA based methods
, Article IRBM ; Volume 36, Issue 1 , 2015 , Pages 20-32 ; 19590318 (ISSN) ; Shamsollahi, M. B ; Albera, L ; Merlet, I ; Sharif University of Technology
Elsevier Masson SAS
2015
Abstract
Denoising is an important preprocessing stage in some ElectroEncephaloGraphy (EEG) applications. For this purpose, Blind Source Separation (BSS) methods, such as Independent Component Analysis (ICA) and Decorrelated and Colored Component Analysis (DCCA), are commonly used. Although ICA and DCCA-based methods are powerful tools to extract sources of interest, the procedure of eliminating the effect of sources of non-interest is usually manual. It should be noted that some methods for automatic selection of artifact sources after BSS methods exist, although they imply a training supervised step. On the other hand, in cases where there are some a prioriinformation about the subspace of...
Online analysis of local field potentials for seizure detection in freely moving rats
, Article Iranian Journal of Basic Medical Sciences ; Volume 23, Issue 2 , 2020 , Pages 173-177 ; Nazari, M ; Shojaei, A ; Raoufy, M. R ; Mirnajafi Zadeh, J ; Sharif University of Technology
Mashhad University of Medical Sciences
2020
Abstract
Objective(s): Seizure detection during online recording of electrophysiological parameters is very important in epileptic patients. In the present study, online analysis of field potential recordings was used for detecting spontaneous seizures in epileptic animals. Materials and Methods: Epilepsy was induced in rats by pilocarpine injection. During the chronic period of the pilocarpine model, local field potential (LFP) recording was run for at least 24 hr. At the same time, video monitoring of the animals was done to determine the real time of seizure occurrence. Both power and sample entropy of LFP were used for online analysis. Results: Obtained results showed that changes in LFP power...