Genetic Fuzzy Approach for detecting Sleep Apnea/Hypopnea Syndrome

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dc.contributor.author Maali, Yashar en_US
dc.contributor.author Al-Jumaily, Adel Ali en_US
dc.contributor.editor Dr. Steve Thatcher en_US
dc.date.accessioned 2012-10-12T03:36:21Z
dc.date.available 2012-10-12T03:36:21Z
dc.date.issued 2011 en_US
dc.identifier 2010004912 en_US
dc.identifier.citation Maali Yashar and Al-Jumaily Adel 2011, 'Genetic Fuzzy Approach for detecting Sleep Apnea/Hypopnea Syndrome', , IEEE, Singapore, , pp. V2-337-V2-340. en_US
dc.identifier.issn 978-1-4244-9252-7 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/19197
dc.description.abstract This paper proposes a genetic fuzzy approach for detecting Apnea/Hypopnea events by using Air flow, thoracic and abdominal respiratory movement signals and Oxygen desaturation as inputs. Results show efficiency of this approach. en_US
dc.language English en_US
dc.publisher IEEE en_US
dc.relation.isbasedon en_US
dc.title Genetic Fuzzy Approach for detecting Sleep Apnea/Hypopnea Syndrome en_US
dc.parent 3rd International Conference on Machine Learning and Computing (ICMLC 2011) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Singapore en_US
dc.identifier.startpage V2-337 en_US
dc.identifier.endpage V2-340 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 080108 en_US
dc.personcode 11064058 en_US
dc.personcode 011083 en_US
dc.percentage 100 en_US
dc.classification.name Neural, Evolutionary and Fuzzy Computation en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom 3rd International Conference on Machine Learning and Computing (ICMLC 2011) en_US
dc.date.activity 20110226 en_US
dc.location.activity Singapore en_US
dc.description.keywords Apnea, Hypopnea, sleep disorder, detection en_US
dc.staffid en_US
dc.staffid 011083 en_US


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