title: Objective differentiation of neonatal EEG background grades using detrended fluctuation analysis.
abstract: A quantitative and objective assessment of background electroencephalograph (EEG) in sick neonates remains an everyday clinical challenge. We studied whether long range temporal correlations quantified by detrended fluctuation analysis (DFA) could be used in the neonatal EEG to distinguish different grades of abnormality in the background EEG activity. Long-term EEG records of 34 neonates were collected after perinatal asphyxia, and their background was scored in 1 h epochs (8 h in each neonate) as mild, moderate or severe. We applied DFA on 15 min long, non-overlapping EEG epochs (n = 1088) filtered from 3 to 8 Hz. Our formal feasibility study suggested that DFA exponent can be reliably assessed in only part of the EEG epochs, and in only relatively short time scales (10-60 s), while it becomes ambiguous if longer time scales are considered. This prompted further exploration whether paradigm used for quantifying multifractal DFA (MF-DFA) could be applied in a more efficient way, and whether metrics from MF-DFA paradigm could yield useful benchmark with existing clinical EEG gradings. Comparison of MF-DFA metrics showed a significant difference between three visually assessed background EEG grades. MF-DFA parameters were also significantly correlated to interburst intervals quantified with our previously developed automated detector. Finally, we piloted a monitoring application of MF-DFA metrics and showed their evolution during patient recovery from asphyxia. Our exploratory study showed that neonatal EEG can be quantified using multifractal metrics, which might offer a suitable parameter to quantify the grade of EEG background, or to monitor changes in brain state that take place during long-term brain monitoring.
authors.affiliation: Department of Electrical Engineering (ESAT), STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven Leuven, Belgium ; iMinds Medical IT Department Leuven, Belgium.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Matic
authors.affiliation: Section of Clinical Neurophysiology, Department of Neurology, Erasmus MC, University Medical Center Rotterdam, The Netherlands.
authors.forename: Perumpillichira Joseph
authors.initials: PJ
authors.lastname: Cherian
authors.affiliation: Department of Electrical Engineering (ESAT), STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven Leuven, Belgium ; iMinds Medical IT Department Leuven, Belgium.
authors.forename: Ninah
authors.initials: N
authors.lastname: Koolen
authors.affiliation: Department of Electrical Engineering (ESAT), STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven Leuven, Belgium ; iMinds Medical IT Department Leuven, Belgium.
authors.forename: Amir H
authors.initials: AH
authors.lastname: Ansari
authors.affiliation: Neonatal Intensive Care Unit, University Hospital Gasthuisberg Leuven, Belgium.
authors.forename: Gunnar
authors.initials: G
authors.lastname: Naulaers
authors.affiliation: Section of Neonatology, Department of Pediatrics, Erasmus MC-Sophia Children's Hospital, University Medical Center Rotterdam, Netherlands.
authors.forename: Paul
authors.initials: P
authors.lastname: Govaert
authors.affiliation: Department of Electrical Engineering (ESAT), STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven Leuven, Belgium ; iMinds Medical IT Department Leuven, Belgium.
authors.forename: Sabine
authors.initials: S
authors.lastname: Van Huffel
authors.affiliation: Department of Engineering, Institute of Biomedical Engineering, University of Oxford Oxford, UK.
authors.forename: Maarten
authors.initials: M
authors.lastname: De Vos
authors.affiliation: Department of Children's Clinical Neurophysiology, HUS Medical Imaging Center and Children's Hospital, Helsinki University Central Hospital and University of Helsinki Helsinki, Finland.
authors.forename: Sampsa
authors.initials: S
authors.lastname: Vanhatalo
keywords: asphyxia; background EEG; brain monitoring; detrended fluctuation analysis; multifractal