|
Title:
|
EEG Windowed statitical wavelet deviation for estimation of muscular artifacts
|
|
Author:
|
Vialatte, François B.; Solé-Casals, Jordi; Cichocki, Andrej
|
|
Other authors:
|
Universitat de Vic. Escola Politècnica Superior; Universitat de Vic. Grup de Recerca en Tecnologies Digitals; International Conference on Acoustics, Speech and Signal Processing (2007 : Honolulu); ICASSP 2007 |
|
Notes:
|
Electroencephalographic (EEG) recordings are, most of
the times, corrupted by spurious artifacts, which should be
rejected or cleaned by the practitioner. As human scalp EEG
screening is error-prone, automatic artifact detection is an issue
of capital importance, to ensure objective and reliable results.
In this paper we propose a new approach for discrimination
of muscular activity in the human scalp quantitative
EEG (QEEG), based on the time-frequency shape analysis.
The impact of the muscular activity on the EEG can be evaluated
from this methodology. We present an application of
this scoring as a preprocessing step for EEG signal analysis,
in order to evaluate the amount of muscular activity for two
set of EEG recordings for dementia patients with early stage
of Alzheimer’s disease and control age-matched subjects. |
|
Subject(s):
|
-Tractament del senyal |
|
Rights:
|
(c) IEEE, 2007 Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Tots els drets reservats
|
|
Document type:
|
Conference Object |
|
Published by:
|
IEEE
|
|
Share:
|
|
