Amplitude-integrated electroencephalography applications and algorithms in neonates: a systematic review

Chen Chen, Chenglu Sun, Steffen Leonhardt, Peter Andriessen, Hendrik Niemarkt, Wei Chen (Corresponding author)

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

6 Citaten (Scopus)
204 Downloads (Pure)


Amplitude-integrated electroencephalography (aEEG) is a simplified method for long-term, continuous, and bedside monitoring of brain activity. While conventional Electroencephalography (EEG) is the gold standard of assessing brain function, aEEG is easy to operate and allows bedside interpretation of brain activity by health care providers without extensive knowledge of neurophysiology. aEEG is increasingly applied in neurological monitoring in neonates, especially in the neonatal intensive care unit (NICU). To a growing extent, researchers and clinicians are convinced that aEEG provides valuable clinical information and can be used to assess the severity of neonatal encephalopathy. Meanwhile, to digitalize the aEEG transformation process and automate the interpretation process, different algorithms have been proposed in the last decades. This paper provides a comprehensive review of aEEG for neonatal monitoring from both clinical and technological perspectives. The paper first reviews the clinical applications of aEEG and discusses the merits and demerits of neonatal aEEG monitoring in terms of the assistance of the treatment and prognosis of cerebral diseases like hypoxic-ischemic encephalopathy (HIE), seizure and so on. And then furthermore, the algorithms to transform EEG into aEEG and the algorithms for aEEG interpretation like the automatic classification of aEEG tracing, automatic seizure detection of aEEG, etc. are reviewed.
Originele taal-2Engels
Pagina's (van-tot)141766-141781
Aantal pagina's16
TijdschriftIEEE Access
StatusGepubliceerd - 30 sep. 2019


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