A novel approach for noise removal and distinction of EEG recordings

Authors: Alharbi

Journal: Biomedical signal processing and control

Volume: 39

Issue: 2018

Publisher: Elsevier BV

ISSN: 1746-8094

This data was imported from Scopus:

Authors: Alharbi, N.

Journal: Biomedical Signal Processing and Control

Volume: 39

Pages: 23-33

eISSN: 1746-8108

ISSN: 1746-8094

DOI: 10.1016/j.bspc.2017.07.011

© 2017 Elsevier Ltd This paper presents a novel approach for the analysis of electroencephalography (EEG) signals. It is based on the distribution of the eigenvalues of a scaled Hankel matrix, which can enable us to determine the number of eigenvalues required for noise removal and signal extraction in singular spectrum analysis. This paper examines the applicability of the approach to discriminate between epileptic seizure and normal EEG signals, the extraction of attractive patterns, the filtering of EEG signals and the elimination of the noise included in the signals. Various criteria are used as features to distinguish between epileptic and normal EEG segments. The results indicate the capability of the approach for noise removal in both EEG signals, and for discrimination between them.

This source preferred by Nader Alharbi

This data was imported from Web of Science (Lite):

Authors: Alharbi, N.

Journal: BIOMEDICAL SIGNAL PROCESSING AND CONTROL

Volume: 39

Pages: 23-33

eISSN: 1746-8108

ISSN: 1746-8094

DOI: 10.1016/j.bspc.2017.07.011

The data on this page was last updated at 04:51 on April 23, 2018.