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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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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


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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