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OBJECTIVE The relevance of the dimensional complexity (DC) for the analysis of sleep EEG data is investigated and compared to linear measures. METHODS We calculated DC of artifact-free 1 min segments of all-night sleep EEG recordings of 4 healthy young subjects. Non-linearity was tested by comparing with DC values of surrogate data. Linear properties of(More)
A new statistical method is described for detecting state changes in the electroencephalogram (EEG), based on the ongoing relationships between electrode voltages at different scalp locations. An EEG sleep recording from one NREM-REM sleep cycle from a healthy subject was used for exploratory analysis. A dimensionless function defined at discrete times ti,(More)
A new algorithm for the detection of oscillatory events in the EEG is presented. By estimating autoregressive (AR) models on short segments the EEG is described as a superposition of harmonic oscillators with damping and frequencies varying in time. Oscillatory events are detected, whenever the damping of one or more frequencies falls below a predefined(More)
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