Pharmacoelectroencephalogra. phy
Main Editor:W.M. Herrm!lnn (Berlin)
Original Paper
Neuropsychobiology 1999;40:150-157
Artifact Processing in Computerized
Analysis of Sieep EEG - A Review
Peter Anderer
a
Stephen Roberts
g
Alois Schlögl
f
Georg Gruber
a
Gerhard Klösch
b
Werner Herrmann
h
Peter Rappelsberger
C
Oliver Filz
d
Manel J. Barbanoji Georg Dorffner
e
Bernd Saletu
a
Departments of ·Psychiatry and bNeurology, and <institute for Neurophysiology, School of Medicine,
University of Vienna, dlnstitute for Information Processing, Austrian Academy of Sciences, and
eAustrian Research Institute for Artificiallntelligence, Vienna, (Department of Medicallnformatics,
University of Technology, Graz, Austria; gDepartment of Electrical and Electronic Engineering, Imperial College,
London, UK; hLaboratory of Clinical Psychophysiology, Department of Psychiatry, Free University of Berlin,
Germany; iDepartment of Pharmacology and Psychiatry, University of Barcelona, Spain
KeyWords
Sieep EEG analysis· Artifact minimization . Artifact
identification
Abstract
Quantitative analysis of sleep EEG data can provide valu-
able additional information in sleep research. However,
analysis of data contaminated by artifacts can lead to
spurious results. Thus, the first step in realizing an auto-
matic sleep analysis system is the implementation of a
reliable and valid artifact processing strategy. This strat-
egy should include: (1) high-quality recording techniques
in order to minimize the occurrence of avoidable artifacts
(e.g. technical artifacts); (2) artifact minimization proce-
dures in order to minimize the loss of data by estimating
the contribution of different artifacts in the EEG record-
ings, thus allowing the calcl!lation ofthe 'corrected' EEG
(e.g. ocular and ECG interference), and finally (3) artifact
identification procedures in order to define epochs con-
taminated by remaining artifacts (e.g. movement and
muscle artifacts). Therefore, after a short description of
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the types of artifacts in the sleep EEG and some typical
examples obtained in different sleep stages, artifact
minimization and identification procedures will be re-
viewed.
Introduction
In reeent years, inereasing efforts have been made to
develop eomputer-assisted sleep analysis systems [for re-
view see 1-3]. In 1993, a consensus report of the EC eon-
eerted action 'Methodology for analysis ofthe sleep-wake-
fulness continuum' was published by Kemp [4], reeom-
mending the use of a standard format for digitized poly-
graphie reeordings (EDF-format, Kemp et al. [5]) and of a
time resolution of 1 s for deseribing sleep/wake-related
signal eharaeteristies on a eontinuous seale. New ap-
proaehes to the automatie analysis of human sleep were
presented by Roberts and Tarassenko [6], Schaltenbrand
et al. [7] and Pardey et al. [8]. Based on these previous
results, a European projeet (,SIESTA - A new standard
DipL·Jng. Peler Anderer
Departmenl ofPsychialry, UniversilY ofVienna
Währinger Gürtel 18-20
A-1090 Vienna (Auslria)
Tel. +43 I 40400 3628, Fax +43 I 4025909, E-Mail peler.anderer@akh·wien.ac.al