Assessing the effectiveness of heart rate variability as a diagnostic tool for brain injuries in infants

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dc.contributor.authorRezaei, Kimiaen
dc.contributor.authorYu, Kaiyuen
dc.contributor.authorMathieson, Sean R.en
dc.contributor.authorFlynn, Andrewen
dc.contributor.authorLightbody, Gordonen
dc.contributor.authorBoylan, Geraldine B.en
dc.contributor.authorMarnane, William P.en
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2025-02-17T16:03:19Z
dc.date.available2025-02-17T16:03:19Z
dc.date.issued2024-12-17en
dc.description.abstractHypoxic-Ischemic Encephalopathy (HIE), marked by cerebral oxygen deprivation, prompts exploration beyond the electroencephalogram (EEG) modality. This study investigates heart rate variability (HRV) to assess its potential for seizure detection and HIE grading for neonates. This study utilizes two annotated datasets from real-world clinical settings. Heart Rate (HR) is calculated from the Electrocardiogram (ECG) signal, which are then denoised and segmented. Sixteen time and frequency domain features are extracted from each HR segment. Employing Random Forest (RF), Support Vector Machine (SVM), and Isolation Forest (IF) classifiers, the investigation addresses the detection of seizure and nonseizure segments in ECG, alongside categorizing HIE severity into two mild and normal or moderate and severe grades. While the patient-independent evaluation of the seizure detection system reveals promising outcomes for specific cases, there is a requirement for further refinement in this aspect and exploration into the correlation between HR and EEG, considering the modest AUC of 68.54 percent gained across the entire dataset. In contrast, the HIE grading results present a more promising scenario, attaining an AUC of 77.13 percent. This emphasizes the efficacy of the HIE grading system as a significant diagnostic tool, suggesting its potential for broader clinical applications.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRezaei, K., Yu, K., Mathieson, S. R., Flynn, A., Lightbody, G., Boylan, G. B. and Marnane, W. P. (2024) 'Assessing the effectiveness of heart rate variability as a diagnostic tool for brain injuries in infants', 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 15-19 July, pp. 1-4. https://doi.org/10.1109/EMBC53108.2024.10782021en
dc.identifier.doihttps://doi.org/10.1109/EMBC53108.2024.10782021en
dc.identifier.endpage4en
dc.identifier.isbn979-8-3503-7149-9en
dc.identifier.isbn979-8-3503-7150-5en
dc.identifier.issn2694-0604en
dc.identifier.issn2375-7477en
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/17052
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartof2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 15-19 July 2024en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Frontiers for the Future::Award/19/FFP/6782/IE/Model based decision support for newborn brain protection/en
dc.rights© 2024, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectElectrocardiogramen
dc.subjectHeart rate variabilityen
dc.subjectHypoxic ischemic encephalopathy gradingen
dc.subjectSeizureen
dc.subjectTime and frequency domain featuresen
dc.subjectRandom forest classifieren
dc.titleAssessing the effectiveness of heart rate variability as a diagnostic tool for brain injuries in infantsen
dc.typeConference itemen
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