Sleepwalking and night terrors are considered to be manifestations of the same nosologic continuum. It has been proposed that a sudden arousal from non-rapid eye movement (NREM) sleep is the cause of these disorders. Benign forms of NREM arousal parasomnias occur frequently in childhood and attenuate in teen years; however, they can persist into or begin in adulthood. The available literature documents high levels of psychopathology in adult patients. Sleepwalking and night terrors are most likely to manifest during the first episode of slow wave sleep, but may also appear any time during NREM sleep. The hypersynchronous delta activity, previously considered to be a hallmark of somnambulism, has proven to be unspecific. Post-arousal EEG activity reveals altered consciousness during sleepwalking and sleep terror episodes. Pathophysiology of NREM arousal parasomnias consists of predisposing factors, which may be a genetically determined tendency for deep sleep, facilitating factors which deepen sleep and increase slow wave sleep, and triggering factors which increase sleep fragmentation, such as stress, environmental or endogenous stimuli, and stimulants. Recently published data on low delta power in the first sleep cycle and slow decline of delta power in successive sleep cycles suggest a chronic inability to sustain slow wave sleep.
We present an open system for sleep staging, based explicitly on the criteria used in visual EEG analysis. Slow waves, theta and alpha waves, sleep spindles and K-complexes are parameterized in terms of time duration, amplitude, and frequency of each waveform by means of the matching pursuit algorithm. It allows the detection of these structures using mostly the criteria from visual EEG analysis. For example, within this framework for the first time we compute directly the relative duration of slow waves, which is a basic parameter in recognition of deep sleep stages. Performance of the system is evaluated on 20 polysomnographic recordings, scored by experienced encephalographers. Seven recordings were scored by more than one expert. Proposed system gives concordance with visual staging close to the inter-expert concordance. The algorithm is implemented in a user-friendly software system for display and analysis of polysomnographic recordings, freely available with complete source code from http://signalml.org/svarog.html .
We present an open, parametric system for automatic detection of EEG artifacts in polysomnographic recordings. It relies on independent parameters reflecting the relative presence of each of the eight types of artifacts in a given epoch. An artifact is marked if any of these parameters exceeds a threshold. These thresholds, set for each parameter separately, can be adjusted via "learning by example" procedure (multidimensional minimization with computationally intensive cost function), which can be used to automatically tune the parameters to new types of datasets, environments or requirements. Performance of the system, evaluated on 103 overnight polysomnographic recordings, revealed concordance with decisions of human experts close to the inter-expert agreement. To make this statement well defined, we review the methodology of evaluation for this kind of detection systems. Complete source code is available from http://eeg.pl; a user-friendly version with Java interface is available from http://signalml.org.
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