Abstract
We investigated the possibility to use the Independent Component
Analysis (ICA) as a method
for preprocessing the sleep EEG data with the aim to improve
detection of sleep spindles - specific phenomena of sleep EEG
recordings prevailingly occurring during the stage 2 of the sleep.
We projected the strengths of individual Independent Components (ICs)
onto the scalp sensors to detect potential spatial localization
of sleep-spindles sources. We used two different algorithms for
ICs separation with aim to compare the fitness of the algorithms in
sleep-spindle detection problem.
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