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01455 am a22001813u 4500 |
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2562 |
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|a dc
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|a Baig, MM
|e author
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|a Gholamhosseini, H
|e author
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|a Harrison, MJ
|e author
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|a Detection and classification of Hypovolaemia during anaesthesia
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|b United States National Library of Medicine/IEEE,
|c 2011-11-16T03:21:52Z.
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|a Proceedings from the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '11), Boston, Massachusetts, USA, pages 357 - 360
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|a 978-1-4244-4122-8/11/
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|a In 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%.
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|a OpenAccess
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|a Conference Contribution
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| 856 |
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|z Get fulltext
|u http://hdl.handle.net/10292/2562
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