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A new quantitative automatic method for the measurement of non‐rapid eye movement sleep electroencephalographic amplitude variability
Author(s) -
FERRI RAFFAELE,
RUNDO FRANCESCO,
NOVELLI LUANA,
TERZANO MARIO G.,
PARRINO LIBORIO,
BRUNI OLIVIERO
Publication year - 2012
Publication title -
journal of sleep research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.297
H-Index - 117
eISSN - 1365-2869
pISSN - 0962-1105
DOI - 10.1111/j.1365-2869.2011.00981.x
Subject(s) - non rapid eye movement sleep , electroencephalography , eye movement , sleep (system call) , audiology , amplitude , psychology , slow wave sleep , sleep spindle , rapid eye movement sleep , neuroscience , medicine , physics , computer science , optics , operating system
Summary The aim of this study was to arrange an automatic quantitative measure of the electroencephalographic (EEG) signal amplitude variability during non‐rapid eye movement (NREM) sleep, correlated with the visually extracted cyclic alternating pattern (CAP) parameters. Ninety‐eight polysomnographic EEG recordings of normal controls were used. A new algorithm based on the analysis of the EEG amplitude variability during NREM sleep was designed and applied to all recordings, which were also scored visually for CAP. All measurements obtained with the new algorithm correlated positively with corresponding CAP parameters. In particular, total CAP time correlated with total NREM variability time ( r = 0.596; P < 1E‐07), light sleep CAP time with light sleep variability time ( r = 0.597; P < 1E‐07) and slow wave sleep CAP time with slow wave sleep variability time ( r = 0.809; P < 1E‐07). Only the duration of CAP A phases showed a low correlation with the duration of variability events. Finally, the age‐related modifications of CAP time and of NREM variability time were found to be very similar. The new method for the automatic analysis of NREM sleep amplitude variability presented here correlates significantly with visual CAP parameters; its application requires a minimum work time, compared to CAP analysis, and might be used in large studies involving numerous recordings in which NREM sleep EEG amplitude variability needs to be assessed.