Sleep EEG composition in the first three months of life in monozygotic and dizygotic twins.

We investigated genetic influence on sleep electroencephalogram (EEG) composition by a classical twin study of monozygotic (MZ) and dizygotic (DZ) twins in the first 3 months of life. Polysomnographic (PSG) recordings were obtained in 10 MZ and 20 DZ twin pairs in the 37th, 46th, and 52nd week of postmenstrual age (PMA). The EEG power spectra were generated on the basis of fast Fourier transformation (FFT).

Automatic classification of infant sleep based on instantaneous frequencies in a single-channel EEG signal.

This study presents a novel approach for the electroencephalogram (EEG) signal quantification in which the empirical mode decomposition method, a time-frequency method designated for nonlinear and non-stationary signals, decomposes the EEG signal into intrinsic mode functions (IMF) with corresponding frequency ranges that characterize the appropriate oscillatory modes embedded in the brain neural activity acquired using EEG. To calculate the instantaneous frequency of IMFs, an algorithm was developed using the Generalized Zero Crossing method. From the resulting frequencies, two different novel features were generated: the median instantaneous frequencies and the number of instantaneous frequency changes during a 30s segment for seven IMFs.