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dc.contributor.authorDunne, Eoghan
dc.contributor.authorSantorelli, Adam
dc.contributor.authorMcGinley, Brian
dc.contributor.authorO'Halloran, Martin
dc.contributor.authorLeader, Geraldine
dc.contributor.authorPorter, Emily
dc.contributor.editorBoyle, Alistair
dc.contributor.editorPolydorides, Nick
dc.contributor.editorJia, Jiabin
dc.date.accessioned2018-07-30T13:12:58Z
dc.date.available2018-07-30T13:12:58Z
dc.date.issued2018-06-11
dc.identifier.citationDunne, Eoghan; Santorelli, Adam; McGinley, Brian; O'Halloran, Martin; Leader, Geraldine; Porter, Emily; (2018) EIT Image-Based Bladder State Classification for Nocturnal Enuresis. In: Boyle, Alistair; Polydorides, Nick; Jia, Jiabin; eds. Proceedings of the 19th International Conference on Biomedical Applications of Electrical Impedance Tomography, Edinburgh, 11/06/2018- 13/06/2018en_IE
dc.identifier.urihttp://hdl.handle.net/10379/7437
dc.description.abstractIn this paper, we propose the use of electrical impedance tomography (EIT) to support children with nocturnal enuresis. We perform the first image-based threshold classification for determining the bladder state of not full or full . The results demonstrate the strong promise for EIT as an aid for nocturnal enuresis.en_IE
dc.description.sponsorshipThis research was supported by the European Research Council under the European Union’s Horizon 2020 Programme/ ERC Grant Agreement BioElecPro n. 637780 and the charity RESPECT and the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA Grant Agreement no. PCOFUND-GA-2013-608728.en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherSchool of Engineering, The University of Edinburghen_IE
dc.relation.ispartof19th International Conference on Biomedical Applications of Electrical Impedance Tomographyen
dc.subjectElectrical Impedance Tomographyen_IE
dc.subjectNocturnal Enuresisen_IE
dc.subjectImage Classificationen_IE
dc.subjectUrinary Bladderen_IE
dc.subjectBladder Fullnessen_IE
dc.titleEIT image-based bladder state classification for nocturnal enuresisen_IE
dc.typeConference Paperen_IE
dc.date.updated2018-07-04T09:30:01Z
dc.identifier.doi10.5281/zenodo.1210247
dc.local.publishedsourcehttp://dx.doi.org/10.5281/zenodo.1210247en_IE
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funderHorizon 2020en_IE
dc.contributor.funderEuropean Research Councilen_IE
dc.contributor.funderRESPECTen_IE
dc.contributor.funderFP7 People: Marie-Curie Actionsen_IE
dc.internal.rssid14583099
dc.local.contactEoghan Dunne, -. - Email: e.dunne13@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionPUBLISHED
dcterms.projectinfo:eu-repo/grantAgreement/EC/H2020::ERC::ERC-STG/637780/EU/Frontier Research on the Dielectric Properties of Biological Tissue/BIOELECPROen_IE
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