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Localizing the neonatal and fetal spontaneous brain activity by hilbert phase analysis

We propose a novel method to characterize the spontaneous brain signals using Hilbert phases. The Hilbert phase of a signal exhibits phase slips when the magnitude of the successive phase difference exceeds π. To this end we use standard deviation (σΔτ) of the time (Aτ) between successive phase slips to characterize the signals. We demonstrate the application of this approach to neonatal and fetal magnetoencephalographic signals recorded using a 151-sensor array to identify the sensors containing the neonatal and fetal brain signals. To this end we propose a spatial filter using σ(Ατ) as weights to reconstruct the brain signals.