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dc.contributor.authorBaig, MM
dc.contributor.authorGholamhosseini, H
dc.contributor.authorHarrison, MJ
dc.date.accessioned2011-11-16T03:21:52Z
dc.date.available2011-11-16T03:21:52Z
dc.date.copyright2011-08-30
dc.date.issued2011-11-16
dc.identifier.citationProceedings from the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC ’11), Boston, Massachusetts, USA, pages 357 - 360
dc.identifier.isbn978-1-4244-4122-8/11/
dc.identifier.urihttp://hdl.handle.net/10292/2562
dc.description.abstractIn recent years, there has been a rapid growth in patient monitoring and medical data analysis using decision support systems, smart alarm monitoring, expert systems and many other computer aided protocols. The main goal of this study was to enhance the developed diagnostic alarm system for detecting critical events during anaesthesia. The proposed diagnostic alarm system is called Fuzzy logic monitoring system-2 (FLMS- 2). The performance of the system was validated through a series of off-line tests. When detecting hypovolaemia a substantial level of agreement was observed between FLMS-2 and the human expert and it is shown that system has a better performance with sensitivity of 94%, specificity of 90% and predictability of 72%.
dc.publisherUnited States National Library of Medicine/IEEE
dc.relation.urihttp://embc2011.embs.org/
dc.rightsCopyright © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.titleDetection and classification of Hypovolaemia during anaesthesia
dc.typeConference Contribution
dc.rights.accessrightsOpenAccess


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