|
Title:
|
Towards Semi-Automatic Artifact Rejection for the Improvement of Alzheimer’s Disease Screening from EEG Signals
|
|
Author:
|
Solé-Casals, Jordi; Vialatte, François B.
|
|
Other authors:
|
Universitat de Vic - Universitat Central de Catalunya. Facultat de Ciències i Tecnologia |
|
Notes:
|
A large number of studies have analyzed measurable changes that Alzheimer’s
disease causes on electroencephalography (EEG). Despite being easily reproducible, those
markers have limited sensitivity, which reduces the interest of EEG as a screening tool for
this pathology. This is for a large part due to the poor signal-to-noise ratio of EEG signals:
EEG recordings are indeed usually corrupted by spurious extra-cerebral artifacts. These
artifacts are responsible for a consequent degradation of the signal quality. We investigate
the possibility to automatically clean a database of EEG recordings taken from patients
suffering from Alzheimer’s disease and healthy age-matched controls. We present here an
investigation of commonly used markers of EEG artifacts: kurtosis, sample entropy,
zero-crossing rate and fractal dimension. We investigate the reliability of the markers, by
comparison with human labeling of sources. Our results show significant differences with
the sample entropy marker. We present a strategy for semi-automatic cleaning based on
blind source separation, which may improve the specificity of Alzheimer screening using
EEG signals |
|
Subject(s):
|
-Alzheimer, Malaltia d' |
|
Rights:
|
Aquest document està subjecte a aquesta llicència Creative Commons
http://creativecommons.org/licenses/by-nc/3.0/es/
|
|
Document type:
|
Article
info:eu-repo/publishedVersion |
|
Published by:
|
MDPI AG
|
|
Share:
|
|
