ArticleFrontiers in human neuroscience2015
Objective differentiation of neonatal EEG background grades using detrended fluctuation analysis.
Article in Frontiers in human neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 39 citations in OpenAlex.
- Neurophysiological changes associated with dysglycemia in term neonates with neonatal encephalopathy.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025Article
- Quantitative EEG features during the first day correlate to clinical outcome in perinatal asphyxia.Pediatric research · 2025Article
- Personalized relapse prediction in patients with major depressive disorder using digital biomarkers.Scientific reports · 2023Article
- Study on the Effect of Judgment Excitation Mode to Relieve Driving Fatigue Based on MF-DFA.Brain sciences · 2022Article
- Characterization of the Functional Dynamics in the Neonatal Brain during REM and NREM Sleep States by means of Microstate Analysis.Brain topography · 2021Article
- Prognostic Value of Continuous Electroencephalogram Delta Power in Neonates With Hypoxic-Ischemic Encephalopathy.Journal of child neurology · 2020Article
- Applications of advanced signal processing and machine learning in the neonatal hypoxic-ischemic electroencephalogram.Neural regeneration research · 2020Article
- Pathogenetical and Neurophysiological Features of Patients with Autism Spectrum Disorder: Phenomena and Diagnoses.Journal of clinical medicine · 2019Review
- Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study.Pediatrics and neonatology · 2019Article
- Interrater and Intrarater Agreement in Neonatal Electroencephalogram Background Scoring.Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society · 2019Article
- Frequency-Specific Fractal Analysis of Postural Control Accounts for Control Strategies.Frontiers in physiology · 2018Article
- Lost in Transition: A Systematic Review of Neonatal Electroencephalography in the Delivery Room-Are We Forgetting an Important Biomarker for Newborn Brain Health?Frontiers in pediatrics · 2017Review
- Decomposing Multifractal Crossovers.Frontiers in physiology · 2017Article
- Effect of electrocardiogram interference on cortico-cortical connectivity analysis and a possible solution.Journal of neuroscience methods · 2016Article
- Editorial: Bridging the gap before and after birth: methods and technologies to explore the functional neural development in humans.Frontiers in human neuroscience · 2015Article
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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