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Moreover, in our study the classification of vigilance states was computed automatically by the EEG-based algorithm VIGALL, whereas certain EEG-patterns in the previous study were detected by individual raters.
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Therefore, the classification of EEG-vigilance stages via VIGALL may assist in identifying clinically relevant variations.
Hence, VIGALL is now based on EEG-power source estimates using LORETA (Low Resolution Brain Electromagnetic Tomography) and enables the classification of EEG-vigilance stages for 1-sec-segments.
VIGALL originally was intended for classification of EEG-vigilance stages during rest and hence it is possible that stages with high theta power during the cognitive performance test within this study were misinterpreted as low subvigil stages B2/3 although they might reflect a higher vigilance stage.
Consequently, individual boundaries of frequency bands could be justified, making the vigilance classification of VIGALL more exact.
And the level of vigilance varies wildly.
The strategy is one of vigilance and engagement.
Happiness is a function of vigilance, of watching yourself.
Many Turks today live in a constant state of vigilance.
They require a great deal of vigilance and checking.
That degree of vigilance has not always been in effect.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com