Automated recognition of sleep stages by electroencephalograms
نویسندگان
چکیده
منابع مشابه
Automated Recognition of Sleep Stages Using Electroencephalograms
The assessment of different sleep stages and their disorders in diseases is an important part of telematic medicine. With an electroencephalogram, the different stages of sleep can be monitored and classified with respect to brain activity. By means of modern data management such as the patient monitor ixTrend, for example, the data can be recorded for long sleep phases and evaluated by a compu...
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Fourier analysis has shown that human electroencephalography (EEG) signals mainly consist of frequencies below 80 Hz. Waves with a frequency below 13Hz are dominant during sleep. Here we find that the fractal dimensions of sleep EEG results in a frequency range of 2Hz to 13Hz have potential to be used as a continuous parameter to characterize sleep status. Our results show that during sleep, th...
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The paper integrates and adapts a range of advanced computational, mathematical and statistical tools for the purpose of analysis of neonate sleep stages based on extensive electroencephalogram (EEG) recordings. The level of brain dysmaturity of a neonate is difficult to assess by direct physical or cognitive examination, but dysmaturity is known to be directly related to the structure of neona...
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The aim of this study was to ascertain the acceptability of sleep-deprived EEGs to parents and their young child. Fifty unselected children having a sleep-deprived EEG were recruited. Data were collected from a sleep diary, a parent questionnaire and the request form of the EEG. Data collected covered developmental, learning and behavioural problems and the acceptability of the sleep-deprived E...
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ژورنال
عنوان ژورنال: Wissenschaftliche Beiträge / Technische Hochschule Wildau
سال: 2015
ISSN: 0949-8214
DOI: 10.15771/0949-8214_2015_1_5