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Updated: Jun 19, 2026
Application of an Amplitude-integrated EEG Monitor (Cerebral Function Monitor) to Neonates
Published on: September 6, 2017
Quantitative analysis of amplitude-integrated electroencephalogram patterns in stable preterm infants, with normal
H J Niemarkt1, P Andriessen, C H L Peters
1Neonatal Intensive Care Unit, Máxima Medical Centre, Veldhoven, The Netherlands.
Insights
Quantitative analysis of amplitude-integrated EEG (aEEG) in preterm infants shows that lower margin amplitude and discontinuous background percentage are key indicators of neurophysiological development. These measures correlate with postmenstrual age, offering a novel way to assess infant neurodevelopment.
Area of Science:
- Neonatal neurology
- Quantitative electroencephalography
- Neurodevelopmental assessment
Background:
- Amplitude-integrated EEG (aEEG) is a feasible method for monitoring cerebral activity in preterm infants.
- Limited quantitative data exists on normal aEEG patterns in this population.
- Automated quantification can provide objective insights into aEEG development.
Purpose of the Study:
- To investigate maturational changes in aEEG patterns in stable preterm infants.
- To utilize automated quantification for analyzing aEEG characteristics.
- To establish quantitative markers for neurophysiological development.
Main Methods:
- Collected weekly aEEG recordings from stable preterm infants (gestational age <32 weeks) with normal 1-year neurological follow-up.
- Quantitatively calculated upper margin amplitude (UMA), lower margin amplitude (LMA), and bandwidth (BW) using expert software.
- Calculated the relative duration of discontinuous background patterns (DC-%) as a measure of neurophysiological activity.
Main Results:
- Gestational age positively correlated with LMA in the first week; DC-% decreased significantly.
- Longitudinal analysis revealed an increase in LMA in all infants.
- Both gestational age and postnatal age independently and equally contributed to LMA and DC-% variations, with postmenstrual age strongly correlating with both.
Conclusions:
- This study presents the first automated quantification of aEEG characteristics in stable preterm infants with normal neurodevelopment.
- Lower margin amplitude (LMA) and discontinuous background percentage (DC-%) are identified as simple, quantitative measures of neurophysiological development.
- These quantitative aEEG measures may serve as valuable tools for evaluating neurodevelopment in infants.
Background:
The amplitude-integrated EEG (aEEG) is feasible for monitoring cerebral activity in preterm infants. However, quantitative data on normal patterns in these infants are limited.
Objective:
To study maturational aEEG changes in a cohort of stable preterm infants by automated quantification.
Methods:
In a cohort of stable preterm infants with gestational age (GA) <32 weeks and normal neurological follow-up at 1 year, weekly 4 h EEG recordings were performed. aEEG traces were obtained from channel C(3)-C(4). The upper margin amplitude (UMA), lower margin amplitude (LMA) and bandwidth (BW) were quantitatively calculated using an expert software system. In addition, the relative duration of discontinuous background pattern (discontinuous background defined as activity with LMA <5 microV, expressed as DC-%) was calculated.
Results:
79 aEEG recordings (4-6 recordings/infant) were obtained in 18 infants. Analysis of the first week recordings demonstrated a strong positive correlation between GA and LMA, while DC-% decreased significantly. Longitudinally, all infants showed increase of LMA. Multivariate analysis showed that GA and postnatal age (PA) both contributed independently and equally to LMA and DC-%. We found a strong correlation between postmenstrual age (GA + PA) and LMA and DC-%, respectively.
Conclusion:
To our knowledge, this is the first study where aEEG development was studied by automated quantification of aEEG characteristics in a cohort of stable preterm infants with a normal neurological development at 1 year of age. LMA and DC-% are simple quantitative measures of neurophysiologic development and may be used to evaluate neurodevelopment in infants.
