Comparison of manual sleep staging with automated neural network-based analysis in clinical practice

  1. Lookup NU author(s)
  2. Jennifer Caffarel
  3. Claire Harrison
  4. Dr Clive Griffiths
  5. Dr Michael Drinnan
Author(s)Caffarel J, Gibson GJ, Harrison P, Griffiths CJ, Drinnan MJ
Publication type Article
JournalMedical and Biological Engineering & Computing
Year2006
Volume44
Issue1-2
Pages105-110
ISSN (print)0140-0118
ISSN (electronic)1741-0444
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We have compared sleep staging by an automated neural network (ANN) system, BioSleep™ (Oxford BioSignals) and a human scorer using the Rechtschaffen and Kales scoring system. Sleep study recordings from 114 patients with suspected obstructed sleep apnoea syndrome (OSA) were analysed by ANN and by a blinded human scorer. We also examined human scorer reliability by calculating the agreement between the index scorer and a second independent blinded scorer for 28 of the 114 studies. For each study, we built contingency tables on an epoch-by-epoch (30 s epochs) comparison basis. From these, we derived kappa (κ) coefficients for different combinations of sleep stages. The overall agreement of automatic and manual scoring for the 114 studies for the classification {wake | light-sleep | deep-sleep | REM} was poor (median κ=0.305) and only a little better (κ=0.449) for the crude {wake | sleep} distinction. For the subgroup of 28 randomly selected studies, the overall agreement of automatic and manual scoring was again relatively low (κ=0.331 for {wake | light-sleep | deep-sleep | REM} and κ=0.505 for {wake | sleep}), whereas inter-scorer reliability was higher (κ=0.641 for {wake | light-sleep | deep-sleep | REM} and κ=0.737 for {wake | sleep}). We conclude that such an ANN-based analysis system is not sufficiently accurate for sleep study analyses using the R&K classification system.
PublisherSpringer
URLhttp://dx.doi.org/10.1007/s11517-005-0002-4
DOI10.1007/s11517-005-0002-4
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