Using the Discrete Hilbert Transform for the comparison between Tracé Alternant and High Voltage Slow patterns extracted from full-term neonatal EEG
This work aims at statistically evaluating the differences between two quiet sleep patterns, Tracé Alternant (TA) and High Voltage Slow (HVS) of EEG signals collected from derivation F4–P4 of 25 full-term newborns. Firstly, 124 artifact-free segments (30 s duration) during TA and 46 during HVS were selected. Then, each segment was filtered (6th order Butterwoth, zero-phase) in three distinct bands: slow delta (0.25–2 Hz), fast delta (2–4 Hz) and theta (4–8 Hz). By applying the Discrete Hilbert Transform (DHT) to these filtered signals, the envelope (A[n]) and the modulus of the instantaneous frequency (|Fi[n]|) were estimated. From these DHT dynamic spectral parameters, the sample distributions were determined and the medians obtained for each data segment. Based on this procedure, the medianvectors of HVS (mHVS) and of TA (mTA) for each parameter and each frequency band were formed. The time evolution of A[n] and |Fi[n]| for any pattern resembles the same characteristics (amplitude and frequency) of the original EEG signal. Moreover, applying the Wilcoxon rank sum test to mHVS and mTA, showed statistically significant differences (α = 0.05) between TA and HVS for A[n] in the three frequency bands. On the other hand, when this test is applied to |Fi[n]|, only the slow delta band presents significant difference. Hence, these findings could be used for distinguishing between HVS and TA.
Keywordsneonatal EEG Sleep patterns Discrete Hilbert Transform
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