dc.contributor.advisor |
Unsworth, P |
en |
dc.contributor.advisor |
Gunn, AJ |
en |
dc.contributor.advisor |
Bennet, L |
en |
dc.contributor.author |
Abbasi, Seyed |
en |
dc.date.accessioned |
2018-06-27T02:53:41Z |
en |
dc.date.issued |
2017 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/37346 |
en |
dc.description.abstract |
Prenatal and neonatal studies around Hypoxia-Ischemic have shown that the brain injury caused by lack of oxygen evolves over time and this evolutionary process provides a window of opportunity for possible treatments for a few hours post HI insult. The motivation of this research was to develop real-time automated algorithms for accurate and reliable identification and quantification of the potential biomarkers of evolving HI brain injury that emerge as particular micro-scale epileptiform HI transients in a profoundly suppressed electroencephalographic (EEG) background, after a severe HI insult; during the period in which the brain injury is still treatable. Hence, this thesis will address the above issues by making three major scientific contributions. The first scientific contribution of this thesis is to introduce a novel heuristic automated technique based on the fusion of Wavelets and template matching classifiers for the reliable identification of the post HI sharp wave transients in the 1024Hz sampled EEG of asphyxiated in utero preterm fetal sheep as a method for examining the adaptations to HI insults. The second scientific contribution of this study demonstrates, for the first time that HI micro-scale sharp wave transients from the in utero preterm sheep models are indeed a biomarker for HI and significantly correlate with subcortical neuronal loss in caudate and the dentate gyrus of the striatum and hippocampus, respectively. The results have advance impact by demonstrating that it is possible to time localize where the occurrence of the automatically identified HI micro-scale sharp waves correlate with brain damage. The last main contribution of this thesis is to demonstrate how advanced signal processing approaches based on the combination of Wavelets-thresholding classifiers can be used for real-time and accurate identification of HI spikes and Stereotypic Evolving Micro-scale Seizures (SEMS) transients. It also assesses the effect of drugs (particularly MgSo4) on the number of automatically identified sharp transients present in the EEG, post HI insult. The results of this thesis emphasize the importance of early identification of the HI micro-scale transients and substantiate where in time is possible to optimally fight against the spread of injury before it becomes irreversible. It is hoped that the findings of this research will be of benefit for future works in this interesting field. |
en |
dc.publisher |
ResearchSpace@Auckland |
en |
dc.relation.ispartof |
PhD Thesis - University of Auckland |
en |
dc.relation.isreferencedby |
UoA99265070411902091 |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.title |
Investigating micro-scale EEG transients as potential biomarkers for early prediction of Hypoxic Ischemia and their relationship to perinatal preterm brain injury |
en |
dc.type |
Thesis |
en |
thesis.degree.discipline |
Engineering Science |
en |
thesis.degree.grantor |
The University of Auckland |
en |
thesis.degree.level |
Doctoral |
en |
thesis.degree.name |
PhD |
en |
dc.rights.holder |
Copyright: The author |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.elements-id |
745813 |
en |
pubs.org-id |
Bioengineering Institute |
en |
pubs.record-created-at-source-date |
2018-06-27 |
en |
dc.identifier.wikidata |
Q112931907 |
|