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Erschienen in: Journal of Clinical Monitoring and Computing 6/2014

01.12.2014 | Original Research

Automatic control of the NMB level in general anaesthesia with a switching total system mass control strategy

verfasst von: Miguel Teixeira, Teresa Mendonça, Paula Rocha, Rui Rabiço

Erschienen in: Journal of Clinical Monitoring and Computing | Ausgabe 6/2014

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Abstract

This paper presents a model based switching control strategy to drive the neuromuscular blockade (NMB) level of patients undergoing general anesthesia to a predefined reference. A single-input single-output Wiener system with only two parameters is used to model the effect of two different muscle relaxants, atracurium and rocuronium, and a switching controller is designed based on a bank of total system mass control laws. Each of such laws is tuned for an individual model from a bank chosen to represent the behavior of the whole population. The control law to be applied at each instant corresponds to the model whose NMB response is closer to the patient’s response. Moreover a scheme to improve the reference tracking quality based on the analysis of the patient’s response, as well as, a comparison between the switching strategy and the Extended Kalman Kilter (EKF) technique are presented. The results are illustrated by means of several simulations, where switching shows to provide good results, both in theory and in practice, with a desirable reference tracking. The reference tracking improvement technique is able to produce a better reference tracking. Also, this technique showed a better performance than the (EKF). Based on these results, the switching control strategy with a bank of total system mass control laws proved to be robust enough to be used as an automatic control system for the NMB level.
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Metadaten
Titel
Automatic control of the NMB level in general anaesthesia with a switching total system mass control strategy
verfasst von
Miguel Teixeira
Teresa Mendonça
Paula Rocha
Rui Rabiço
Publikationsdatum
01.12.2014
Verlag
Springer Netherlands
Erschienen in
Journal of Clinical Monitoring and Computing / Ausgabe 6/2014
Print ISSN: 1387-1307
Elektronische ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-013-9500-3

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