Visual and automatic cyclic alternating pattern (CAP) scoring

Visual and automatic cyclic alternating pattern (CAP) scoring

Author Rosa, Agostinho Google Scholar
Alves, Gabriela Rodrigues Autor UNIFESP Google Scholar
Brito, Magneide Autor UNIFESP Google Scholar
Lopes, Maria Cecilia Autor UNIFESP Google Scholar
Tufik, Sergio Autor UNIFESP Google Scholar
Institution Univ Tecn Lisboa
Universidade Federal de São Paulo (UNIFESP)
Abstract The classification of short duration events in the EEG during sleep, as the A stage of the cyclic alternating pattern (CAP) is a tedious and error prone task. the number of events under normal conditions is large (several hundreds), and it is necessary to mark the limits of the events with precision, otherwise the time sensitive classification of the CAP phases (A and B) and specially the scoring of different types of A phases will be compromised. the objective of this study is to verify the feasibility of visual CAP scoring with only one channel of EEG, the evaluation of the inter-scorer agreement in a variety of recordings, and the comparison of the visual scorings with a known automatic scoring system. Sixteen hours of one channel (C4-A1 or C3-A2) of NREM sleep were extracted from eight whole night recordings in European Data Format and presented to the different scorers. the average inter-scorer agreement for all scorers is above 70%, the pair wise inter-scorer agreement found was between 69% up to 77.5%. These values are similar to what has been reported in different type studies. the automatic scoring system has similar performance of the visual scorings. the study also has shown that it is possible to classify the CAP using only one channel of EEG.
Keywords cyclic alternating pattern
visual scoring
automatic scoring
Language English
Date 2006-09-01
Published in Arquivos de Neuro-psiquiatria. São Paulo, SP: Assoc Arquivos Neuro- Psiquiatria, v. 64, n. 3A, p. 578-581, 2006.
ISSN 0004-282X (Sherpa/Romeo, impact factor)
Publisher Assoc Arquivos Neuro- Psiquiatria
Extent 578-581
Access rights Open access Open Access
Type Article
Web of Science ID WOS:000240614200008
SciELO ID S0004-282X2006000400008 (statistics in SciELO)

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