HMM based sensor fault detection in neuromuscular blockade control

The problem of embedding sensor fault tolerance in the control of neuromuscular blockade of patients subject to anesthesia for surgery is considered. A hidden Markov model whose state, assumed unavailable for direct observation, is estimated using a nonlinear filtering algorithm (special case of Bau...

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Published inECC : 2007 European Control Conference : 2-5 July 2007 pp. 2547 - 2553
Main Authors Lemos, Joao M., Magalhaes, Hugo, Mendonca, Teresa
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.07.2007
Subjects
Algorithms
Anaesthesia
Anesthesia
Biomedical measurement
Biomedicine
Blocking
Control Applications
Fault Tolerant Control
Faults
Filtering
Filtration
Hidden Markov models
HMM
Markov models
Markov processes
Neuromuscular
Neuromuscular Blockade
Sensors
Surgery
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ISBN3952417386
9783952417386
DOI10.23919/ECC.2007.7068842

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Summary:The problem of embedding sensor fault tolerance in the control of neuromuscular blockade of patients subject to anesthesia for surgery is considered. A hidden Markov model whose state, assumed unavailable for direct observation, is estimated using a nonlinear filtering algorithm (special case of Baum's algorithm), is proposed for detecting the faults. The resulting algorithm is illustrated by simulations with realistic models of neuromuscular blockade.
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ISBN:3952417386
9783952417386
DOI:10.23919/ECC.2007.7068842