Research article summary:

Modeling for neuromonitoring depth of anesthesia.

Abstract Extract:
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 ... (Full abstract text below)

Published 2002 in Journal: Crit Rev Biomed Eng (Language : eng)

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1. Crit Rev Biomed Eng. 2002 ;30(1-3):131-73

Modeling for neuromonitoring depth of anesthesia.

Zhang XS, Huang JW, Roy RJ

Siemens Medical Solutions USA, Inc., Danvers, Massachusetts, USA.

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.

PMID : 12650289 [PubMed - Indexed for MEDLINE]

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Full Author Information

First Name	LastName	Initials
Xu-Sheng	Zhang	XS
Johnnie W	Huang	JW
Rob J	Roy	RJ

Affiliation: Siemens Medical Solutions USA, Inc., Danvers, Massachusetts, USA.

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