Heart rate variability time-frequency analysis for newborn seizure detection

Mostefa Mesbah, Boualem Boashash, Malarvili Balakrishnan, Paul B. Coldiz

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

The identification of newborn seizures requires the processing of a number of physiological signals routinely recorded from patients, including the EEG and ECG, as well as EOG and respiration signals. Most existing studies have focused on using the EEG as the sole information source in automatic seizure detection. Some of these studies concluded that the information obtained from the EEG should be supplemented by other information obtained from other recorded physiological signals. This chapter documents an approach that uses the ECG as the basis for seizure detection and explores how such approach could be combined with the EEG based methodologies to achieve a robust automatic seizure detector.

Original languageEnglish
Title of host publicationAdvanced Biosignal Processing
PublisherSpringer Berlin Heidelberg
Pages95-121
Number of pages27
ISBN (Print)9783540895053
DOIs
Publication statusPublished - 2009

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Mesbah, M., Boashash, B., Balakrishnan, M., & Coldiz, P. B. (2009). Heart rate variability time-frequency analysis for newborn seizure detection. In Advanced Biosignal Processing (pp. 95-121). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-89506-0_5