Quantitative preterm EEG analysis: The need for caution in using modern data science techniques
dc.contributor.author | O'Toole, John M. | |
dc.contributor.author | Boylan, Geraldine B. | |
dc.contributor.funder | Science Foundation Ireland | en |
dc.date.accessioned | 2019-11-19T12:04:27Z | |
dc.date.available | 2019-11-19T12:04:27Z | |
dc.date.issued | 2019-05-03 | |
dc.description.abstract | Haemodynamic changes during neonatal transition increase the vulnerability of the preterm brain to injury. Real-time monitoring of brain function during this period would help identify the immediate impact of these changes on the brain. Neonatal EEG provides detailed real-time information about newborn brain function but can be difficult to interpret for non-experts; preterm neonatal EEG poses even greater challenges. An objective quantitative measure of preterm brain health would be invaluable during neonatal transition to help guide supportive care and ultimately protect the brain. Appropriate quantitative measures of preterm EEG must be calculated and care needs to be taken when applying the many techniques available for this task in the era of modern data science. This review provides valuable information about the factors that influence quantitative EEG analysis and describes the common pitfalls. Careful feature selection is required and attention must be paid to behavioural state given the variations encountered in newborn EEG during different states. Finally, the detrimental influence of artefacts on quantitative EEG analysis is illustrated. | en |
dc.description.sponsorship | 15/SIRG/3580 | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Published Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.articleid | 174 | en |
dc.identifier.citation | Boylan, G.B. and O'Toole, J.M., 2019. Quantitative preterm EEG analysis: the need for caution in using modern data science techniques. Frontiers in pediatrics, 7, (174). DOI:10.3389/fped.2019.00174 | en |
dc.identifier.doi | 10.3389/fped.2019.00174 | en |
dc.identifier.eissn | 2296-2360 | |
dc.identifier.endpage | 11 | en |
dc.identifier.journaltitle | Frontiers in Pediatrics | en |
dc.identifier.startpage | 1 | en |
dc.identifier.uri | https://hdl.handle.net/10468/9075 | |
dc.identifier.volume | 7 | en |
dc.language.iso | en | en |
dc.publisher | Frontiers Media | en |
dc.relation.project | info:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2272/IE/Irish Centre for Fetal and Neonatal Translational Research (INFANT)/ | en |
dc.relation.uri | https://www.frontiersin.org/articles/10.3389/fped.2019.00174 | |
dc.rights | © 2019 O'Toole and Boylan | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
dc.subject | EEG analysis | en |
dc.subject | Preterm | en |
dc.subject | Neonatal | en |
dc.subject | Data science techniques | en |
dc.title | Quantitative preterm EEG analysis: The need for caution in using modern data science techniques | en |
dc.type | Article (peer-reviewed) | en |