Marco Carrozzi1, Agostino Accardo, Furio Bouquet. 1. UO di Neuropsichiatria Infantile, IRCSS Burlo Garofolo, Via dell'Istria 65/1, I34100 Trieste, Italy. carrozzi@burlo.trieste.it
Abstract
STUDY OBJECTIVES: In this work, we studied the behavior of the fractal dimension during each of the neonatal electroencephalogram (EEG) sleep phases and during the awake state, comparing the results with those of the classical spectral parameters and with zero crossing values. DESIGN: Fractal dimension, zero crossing, and spectral parameters of the EEG bands were determined for each 2-second frame of the EEG sleep-time series. Eight channels of each EEG recording were examined. PARTICIPANTS: Twenty healthy full-term newborns (10 boys and 10 girls) with normal psychomotor development evaluated at 24 and 36 months of age, were chosen to participate in this study. MEASUREMENTS AND RESULTS: Fractal analysis showed that where rhythmic and regular activity are present, as during quiet sleep, the fractal dimension is low and rises when bioelectric activity is more variable and complex, reaching its maximum value during wakefulness. The discriminative value of this parameter was similar to that of some spectral bands. CONCLUSIONS: This work was an initial attempt to apply techniques derived from the nonlinear deterministic studies used to evaluate system complexity, to the neonatal EEG, in order to acquire a normative database that can be used as a reference in neurological pathologies. Fractal dimension alone or together with zero crossing and theta and delta bands could be used for computerized discrimination of neonatal EEG sleep phases.
STUDY OBJECTIVES: In this work, we studied the behavior of the fractal dimension during each of the neonatal electroencephalogram (EEG) sleep phases and during the awake state, comparing the results with those of the classical spectral parameters and with zero crossing values. DESIGN: Fractal dimension, zero crossing, and spectral parameters of the EEG bands were determined for each 2-second frame of the EEG sleep-time series. Eight channels of each EEG recording were examined. PARTICIPANTS: Twenty healthy full-term newborns (10 boys and 10 girls) with normal psychomotor development evaluated at 24 and 36 months of age, were chosen to participate in this study. MEASUREMENTS AND RESULTS: Fractal analysis showed that where rhythmic and regular activity are present, as during quiet sleep, the fractal dimension is low and rises when bioelectric activity is more variable and complex, reaching its maximum value during wakefulness. The discriminative value of this parameter was similar to that of some spectral bands. CONCLUSIONS: This work was an initial attempt to apply techniques derived from the nonlinear deterministic studies used to evaluate system complexity, to the neonatal EEG, in order to acquire a normative database that can be used as a reference in neurological pathologies. Fractal dimension alone or together with zero crossing and theta and delta bands could be used for computerized discrimination of neonatal EEG sleep phases.