Literature DB >> 19705179

A state transition-based method for quantifying EEG sleep fragmentation.

Vinayak Swarnkar1, Udantha R Abeyratne, Craig Hukins, Brett Duce.   

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.

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Year:  2009        PMID: 19705179     DOI: 10.1007/s11517-009-0524-2

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  20 in total

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8.  An alternative measure of sleep fragmentation in clinical practice: the sleep fragmentation index.

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  9 in total

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Journal:  Sleep       Date:  2010-12       Impact factor: 5.849

6.  Objective measure of sleepiness and sleep latency via bispectrum analysis of EEG.

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9.  Labile sleep promotes awareness of abstract knowledge in a serial reaction time task.

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  9 in total

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