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Critical Reviews™ in Biomedical Engineering
SJR: 0.207 SNIP: 0.376 CiteScore™: 0.79

ISSN Imprimer: 0278-940X
ISSN En ligne: 1943-619X

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Volume 47, 2019 Volume 46, 2018 Volume 45, 2017 Volume 44, 2016 Volume 43, 2015 Volume 42, 2014 Volume 41, 2013 Volume 40, 2012 Volume 39, 2011 Volume 38, 2010 Volume 37, 2009 Volume 36, 2008 Volume 35, 2007 Volume 34, 2006 Volume 33, 2005 Volume 32, 2004 Volume 31, 2003 Volume 30, 2002 Volume 29, 2001 Volume 28, 2000 Volume 27, 1999 Volume 26, 1998 Volume 25, 1997 Volume 24, 1996 Volume 23, 1995

Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.v30.i123.70
pages 131-173

Modeling for Neuromonitoring Depth of Anesthesia

Xu-Sheng Zhang
Siemens Medical Solutions USA, Inc., Danvers, Massachusetts
Johnnie W. Huang
Siemens Medical Solutions USA, Inc., Danvers, Massachusetts
Rob J. Roy
Department of Anesthesiology, Albany Medical College, Albany, New York and Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York

RÉSUMÉ

This article reviews the various modeling techniques for neuromonitoring depth of anesthesia (DOA). Traditional techniques such as parametric, predictive, optimal, and adaptive modeling; proportional, integral, derivative (PID) modeling; together with modern techniques such as bispectral-based, artificial neural-network-based, fuzzy logic, and neuro-fuzzy modeling, bring us to the current state of the art in DOA neuromonitoring. This article reviews historical information about each of the modern techniques and provides an example demonstrating its implementation; reviews drug pharmacokinetic/pharmacodynamic (PK/PD) and drug interaction PK/PD modeling techniques for a balanced total intravenous anesthesia (TIVA) administration; and discusses the existing technical problems and clinical challenges, suggesting new techniques necessary for the future development of a DOA monitoring and control system.


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