Quantitative topographic differentiation of the neonatal EEG.
OBJECTIVE
To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'.


METHODS
21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG). From each EEG record, two 5-min samples (one from the middle of quiet sleep, the other from the middle of active sleep) were subject to subsequent automatic analysis and were described by 13 variables: spectral features and features describing shape and variability of the signal. The data from individual infants were averaged and the number of variables was reduced by factor analysis.


RESULTS
All factors identified by factor analysis were statistically significantly influenced by the location of derivation. A large number of statistically significant differences were also established when comparing the effects of individual derivations on each of the 13 measured variables. Both spectral features and features describing shape and variability of the signal are largely accountable for the topographic differentiation of the neonatal EEG.


CONCLUSIONS
The presented method of the automatic EEG analysis is capable to assess the topographic characteristics of the neonatal EEG, and it is adequately sensitive and describes the neonatal electroencephalogram with sufficient precision.


CONCLUSIONS
The discriminatory capability of the used method represents a promise for their application in the clinical practice.
Paul
Karel
K
Institute for the Care of Mother and Child, Prague, Czech Republic. karelpaul@seznam.cz
Krajca
Vladimír
V
Roth
Zdenek
Z
Melichar
Jan
J
Petránek
Svojmil
S
D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004569:Electroencephalography; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D008297:Male; D012894:Sleep Stages / Q000502:physiology