Application of Quantitative Methods of Signal Processing to Automatic Classification of Long-Term EEG Records

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03102015" target="_blank" >RIV/68407700:21230/04:03102015 - isvavai.cz</a>
Alternative codes found
RIV/00064211:_____/04:#0000062
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Application of Quantitative Methods of Signal Processing to Automatic Classification of Long-Term EEG Records
Original language description
The aim the work described in the paper has been to develop a system for processing long-term EEG recordings, especially of comatose state EEG. However with respect to the signal character, the developed approach is suitable for analysis of sleep and newborn EEG too. EEG signal can be analysed both in time and frequency domains. In time domain the basic descriptive quantities are general and central moments of lower orders, in frequency domain the most frequently used method is Fourier transform. For segmentation, combination of non-adaptive an d adaptive segmentation has been used. The approach has been tested on real sleep EEG recording for which the classification has be known. The core of the developed system is the training set on which practically depends the quality of classification. The training set containing 319 segments classified into 10 classes has been used for classification of the 2hour sleep EEG recording.
Czech name
Není k dispozici
Czech description
Není k dispozici

Project
<a href="/en/project/NF7511" target="_blank" >NF7511: Automatic EEG analysis during long-term monitoring in neurological ICU.</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2004
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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