A state transition-based method for quantifying EEG sleep fragmentation

Swarnkar, Vinayak, Abeyratne, Udantha R., Hukins, Craig and Duce, Brett (2009) A state transition-based method for quantifying EEG sleep fragmentation. Medical and Biological Engineering & Computing, 47 10: 1053-1061. doi:10.1007/s11517-009-0524-2

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Author Swarnkar, Vinayak
Abeyratne, Udantha R.
Hukins, Craig
Duce, Brett
Title A state transition-based method for quantifying EEG sleep fragmentation
Journal name Medical and Biological Engineering & Computing   Check publisher's open access policy
ISSN 0140-0118
Publication date 2009-08-01
Year available 2009
Sub-type Article (original research)
DOI 10.1007/s11517-009-0524-2
Open Access Status
Volume 47
Issue 10
Start page 1053
End page 1061
Total pages 9
Editor Jos A. Spaan
Place of publication Germany
Publisher Springer
Language eng
Subject 090303 Biomedical Instrumentation
861502 Medical Instruments
970109 Expanding Knowledge in Engineering
C1
Abstract Sleep fragmentation is the predominant factor causing excessive daytime sleepiness in diseases such as sleep apnea and periodic leg movement syndrome. The reference standard for quantifying sleep fragmentation is the arousal index (ArI), which is defined as the average number of arousals per hour of sleep. Arousal scoring is tedious and subjective resulting in considerable inter- and intra-rater variability. Moreover, ArI is only weakly correlated with other indicators of sleep fragmentation such as the total sleep time (TST) and the sleep efficiency (SE). This introduces consistency problems, making the ArI difficult to interpret in practice. In this article, we address these issues by proposing a novel measure of sleep fragmentation termed the weighted-transition sleep fragmentation index (chi). This new measure is derived by capturing the different sleep states transitions and assigning weights to them. A significant correlation was found between chi and all other indices of sleep fragmentation (r = 0.72, sigma = 0.0001, r = -0.59, sigma = 0.001, r = -0.72, sigma = 0.0001, respectively, for ArI, TST and SE. These results suggest that chi is an accurate and useful tool for clinical practice.
Keyword Sleep fragmentation
Arousal index
Sleep apnea
Periodic leg movement syndrome
Electroencephalographic signals
DAYTIME SLEEPINESS
APNEA
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2010 Higher Education Research Data Collection
School of Information Technology and Electrical Engineering Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 12 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 11 times in Scopus Article | Citations
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Created: Thu, 12 Nov 2009, 21:57:59 EST by Mr Andrew Martlew on behalf of School of Information Technol and Elec Engineering