Andrzej Wakarow

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Electroencephalogram (EEG) provides important and unique information about the sleeping brain. Polysomnography was the major method of sleep analysis and the main diagnostic tool in sleep medicine. The standard interpretation of polysomnographic recordings describes their macrostructure in terms of sleep stages, delineated according to R&K scoring(More)
We propose a new framework for quantitative analysis of sleep EEG, compatible with the traditional analysis, based upon adaptive time-frequency approximation of signals. Using a high resolution description of EEG rhythms and transients in terms of their time occurrence and width, frequency and amplitude, we present a detailed detection and parameterization(More)
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(More)
Adaptive time-frequency approximations, implemented via the matching pursuit algorithm, offer description of local signals structures in terms of their time occurrence and width, frequency and amplitude. This allows to construct explicit filters for finding EEG waveforms, known from the visual analysis, in the matching pursuit decomposition of signals. In(More)
UNLABELLED 34 patients with diagnosis of depressive episode (ICD-10) were treated for 8 weeks with tricyclic antidepressants (TCA) 22 patients were treated with clomipramine 75-175 mg daily, 11 with imipramine 75-150 mg and 1 with amitriptyline 150 mg. Following parameters were analysed: plasma concentration (FPIA, HPLC), pharmaco-EEG (spectrum power for(More)
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