A model-based control scheme for depth of hypnosis in anesthesia
dc.contributor.author | Merigo, L. | |
dc.contributor.author | Padula, Fabrizio | |
dc.contributor.author | Pawlowski, A. | |
dc.contributor.author | Dormido, S. | |
dc.contributor.author | Guzmán Sánchez, J. | |
dc.contributor.author | Latronico, N. | |
dc.contributor.author | Paltenghi, M. | |
dc.contributor.author | Visioli, A. | |
dc.date.accessioned | 2018-04-30T02:39:33Z | |
dc.date.available | 2018-04-30T02:39:33Z | |
dc.date.created | 2018-04-16T07:41:35Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Merigo, L. and Padula, F. and Pawlowski, A. and Dormido, S. and Guzmán Sánchez, J. and Latronico, N. and Paltenghi, M. et al. 2018. A model-based control scheme for depth of hypnosis in anesthesia. Biomedical Signal Processing and Control. 42: pp. 216-229. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/66178 | |
dc.identifier.doi | 10.1016/j.bspc.2018.01.023 | |
dc.description.abstract |
© 2018 Elsevier Ltd. In this paper we propose a model-based scheme to control the depth of hypnosis in anesthesia that uses the BIS signal as controlled variable. In particular, the control scheme exploits the propofol pharmacokinetics/pharmacodynamics model of the patient so that the estimated effect-site concentration is used as a feedback signal for a standard PID controller, which compensates for the model uncertainties. The tuning of the parameters is performed off-line using genetic algorithms to minimize a performance index over a given data set of patients. The effectiveness of the proposed method is verified by means of a Monte Carlo method that takes into account both the intra-patient and inter-patient variability. In general, we obtain a fast induction phase with limited overshoot and a good disturbance rejection during maintenance of anesthesia. | |
dc.title | A model-based control scheme for depth of hypnosis in anesthesia | |
dc.type | Journal Article | |
dcterms.source.volume | 42 | |
dcterms.source.startPage | 216 | |
dcterms.source.endPage | 229 | |
dcterms.source.issn | 1746-8094 | |
dcterms.source.title | Biomedical Signal Processing and Control | |
curtin.department | School of Electrical Engineering, Computing and Mathematical Science (EECMS) | |
curtin.accessStatus | Fulltext not available |
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