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MEEGIPS—A modular EEG investigation and processing system for visual and automated detection of high frequency oscillations

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dc.contributor Háskólinn á Akureyri
dc.contributor University of Akureyri
dc.contributor.author Höller, Peter
dc.contributor.author Trinka, Eugen
dc.contributor.author Höller, Yvonne
dc.date.accessioned 2019-04-26T14:22:44Z
dc.date.available 2019-04-26T14:22:44Z
dc.date.issued 2019-04-05
dc.identifier.citation Höller P, Trinka E and Höller Y (2019) MEEGIPS—A Modular EEG Investigation and Processing System for Visual and Automated Detection of High Frequency Oscillations. Front. Neuroinform. 13:20. doi: 10.3389/fninf.2019.00020
dc.identifier.issn 1662-5196
dc.identifier.uri https://hdl.handle.net/20.500.11815/1147
dc.description.abstract High frequency oscillations (HFOs) are electroencephalographic correlates of brain activity detectable in a frequency range above 80 Hz. They co-occur with physiological processes such as saccades, movement execution, and memory formation, but are also related to pathological processes in patients with epilepsy. Localization of the seizure onset zone, and, more specifically, of the to-be resected area in patients with refractory epilepsy seems to be supported by the detection of HFOs. The visual identification of HFOs is very time consuming with approximately 8 h for 10 min and 20 channels. Therefore, automated detection of HFOs is highly warranted. So far, no software for visual marking or automated detection of HFOs meets the needs of everyday clinical practice and research. In the context of the currently available tools and for the purpose of related local HFO study activities we aimed at converging the advantages of clinical and experimental systems by designing and developing a comprehensive and extensible software framework for HFO analysis that, on the one hand, focuses on the requirements of clinical application and, on the other hand, facilitates the integration of experimental code and algorithms. The development project included the definition of use cases, specification of requirements, software design, implementation, and integration. The work comprised the engineering of component-specific requirements, component design, as well as component- and integration-tests. A functional and tested software package is the deliverable of this activity. The project MEEGIPS, a Modular EEG Investigation and Processing System for visual and automated detection of HFOs, introduces a highly user friendly software that includes five of the most prominent automated detection algorithms. Future evaluation of these, as well as implementation of further algorithms is facilitated by the modular software architecture.
dc.description.sponsorship This work was supported by the Austrian Science Fund (FWF): KLI 657-B31 and by the PMU-FFF: A-18/01/029-HÖL.
dc.language.iso en
dc.publisher Frontiers Media SA
dc.relation.ispartofseries Frontiers in Neuroinformatics;13(20)
dc.rights info:eu-repo/semantics/openAccess
dc.subject Biomedical Engineering
dc.subject Neuroscience (miscellaneous)
dc.subject Computer Science Applications
dc.subject Verkfræði
dc.subject Taugavísindi
dc.subject Hugbúnaður
dc.subject Heilbrigðisvísindi
dc.title MEEGIPS—A modular EEG investigation and processing system for visual and automated detection of high frequency oscillations
dc.type info:eu-repo/semantics/article
dc.description.version Peer reviewed
dc.identifier.journal Frontiers in Neuroinformatics
dc.identifier.doi 10.3389/fninf.2019.00020
dc.relation.url https://www.frontiersin.org/article/10.3389/fninf.2019.00020/full
dc.contributor.department Sálfræðideild (HA)
dc.contributor.department Faculty of Psychology (UA)
dc.contributor.school Hug- og félagsvísindasvið (HA)
dc.contributor.school School of Humanities and Social Sciences (UA)


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