Automated Detection of Anesthetic Depth Levels Using Chaotic Features with Artificial Neural Networks

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Automated Detection of Anesthetic Depth Levels Using Chaotic Features with Artificial Neural Networks

Monitoring the depth of anesthesia (DOA) during surgery is very important in order to avoid patients' interoperative awareness. Since the traditional methods of assessing DOA which involve monitoring the heart rate, pupil size, sweating etc, may vary from patient to patient depending on the typ...

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Bibliographic Details
Main Authors:	Lalitha, V., Eswaran, C.
Format:	Article
Language:	English
Published:	SPRINGER 2007
Subjects:	T Technology (General) QA75.5-76.95 Electronic computers. Computer science
Online Access:	http://shdl.mmu.edu.my/2975/ http://shdl.mmu.edu.my/2975/1/1006.pdf

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