Abstract
Introduction: Reliable polysomnographic classification is
the basis for evaluation of sleep disorders in neurological
diseases.
Aim: To develop a fully automatic sleep scoring algorithm
on the basis of a reproduction of new international sleep
scoring criteria from the American Academy of Sleep
Medicine (AASM).
Methods: A biomedical signal processing algorithm was
developed, allowing for automatic sleep depth quantification
of routine polysomnographic (PSG) recordings through
feature extraction, supervised probabilistic Bayesian
classification, and heuristic rule-based smoothing. The
performance of the algorithm was tested using 28 manually
classified day-night PSGs from 18 normal subjects and 10
patients with Parkinson's disease (PD) or multiple system
atrophy (MSA). This led to quantification of automaticversus-
manual epoch-by-epoch agreement rates for both
normal and abnormal recordings.
Results: Resulting average agreement rates were 87.7%
(Cohen’s Kappa: 0.79) and 68.2%(Cohen’s Kappa: 0.26) in
the normal and abnormal group, respectively. Based on an
observed reliability of the manual scorer of 92.5% (Cohen’s
Kappa: 0.87) in the normal group and 85.3% (Cohen’s
Kappa: 0.73) in the abnormal group.
Conclusion: The developed algorithm was capable of
scoring normal sleep with an accuracy around the manual
inter-scorer reliability, it failed in accurately scoring
abnormal sleep as encountered for the PD/MSA patients,
which is due to the abnormal micro- and macrostructure
pattern in these patients.
Original language | English |
---|---|
Journal | European Journal of Neurology |
Volume | 17 |
Issue number | Supplement s3 |
Pages (from-to) | 624 |
ISSN | 1351-5101 |
DOIs | |
Publication status | Published - 2010 |
Event | 14th Congress of European Federation of Neurological Societies - Geneva, Switzerland Duration: 25 Sept 2010 → 28 Sept 2010 Conference number: 14 http://www2.kenes.com/efns2010/pages/home.aspx |
Conference
Conference | 14th Congress of European Federation of Neurological Societies |
---|---|
Number | 14 |
Country/Territory | Switzerland |
City | Geneva |
Period | 25/09/2010 → 28/09/2010 |
Internet address |