Browsing by Author "Bras, Susana"
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- Controlling the hypnotic drug (propofol) to maintain a stable depth of anesthesia, in dogsPublication . Bras, Susana; Ribeiro, Lenio; Ferreira, David A.; Antunes, Luis; Nunes, Catarina S.The development of control and automatic systems is important to guarantee a stable anesthesia, with no under or over dosage, and no awareness episodes. In this study a controller for the Cerebral State Index (CSI — an electroencephalogram derived signal) was developed. This study was a simulation study, the CSI was modeled using a fuzzy logic model with two inputs the effect-site concentration of propofol and the electromyography (EMG). The controller was tested using constant and variable references in an exhaustive set of simulations. The controller developed presents a good performance in all simulations and the controlled variable seems to be influenced by electromyography level. A controller for propofol anesthesia for veterinary use is an important step towards the improvement of animal welfare. The overall aim is to improve animal safety and comfort.
- Modeling anesthetic drugs' pharmacodynamic interaction on the bispectral index of the EEG: the influence of heart ratePublication . Nunes, Catarina S.; Mendonca, Teresa; Bras, Susana; Ferreira, David A.; Amorim, PedroThe effect of drugs’ interaction on the brain signal Bispectral Index (BIS) is of great importance for an anesthesia control drug infusion system. In this study, the objective was to inspect the influence of patient’s heart rate on the effect of the drugs on BIS. With this goal, the patient’s heart rate was incorporated in an drug interaction model. The model was fitted per patient during anesthesia induction, and tested for prediction under surgery. The results showed that the model with time changing parameters incorporating patient’s heart rate has a better performance than a non adjusted model. Three clusters of models were also identified using the fuzzy cmeans algorithm. These clusters will help to distinguish between different patients’ dynamics.
- Nonlinear modeling of cerebral state index in dogsPublication . Bras, Susana; Bressan, Nadja; Ribeiro, Lenio; Ferreira, David A.; Antunes, Luis; Nunes, Catarina S.The Cerebral State Index (CSI) is an electroencephalogram derived signal representing the depression of central nervous activity produced by anesthetic drugs. In this study, a nonlinear model was developed to describe the CSI tendency during general anesthesia in dogs, by evaluating the effect of the anesthetic drug propofol. The model was based on a compartmental and Hill Equation structure with individually identified parameters. The clinical data of 14 dog surgeries were collected and used for modeling and testing. The model presented good results, following the CSI trend. A model for drug-effect for veterinarian anesthesia is an important step when developing advisory, educational and control systems. The overall aim is to improve animal safety and comfort.
- Synchronization software for automation in anesthesiaPublication . Bressan, Nadja; Castro, Ana; Bras, Susana; Oliveira, Helder P.; Ribeiro, Lenio; Ferreira, David A.; Antunes, Luis; Amorim, Pedro; Nunes, Catarina S.This work presents the development of a software for data acquisition and control (ASYS) on a clinical setup. Similar to the industrial Supervisory Control And Data Acquisition (SCADA) the software assembles a Target Controlled Infusion (TCI) monitoring and supervisory control data in real time from devices in a surgical room. The software is not a full controller since the TCI systems comprehend permanent interaction from the anesthesiologist. Based on pharmacokinetic models, the effect-site and plasma concentrations can be related with the drug dose infused and vice versa. The software determines the infusion rates of the drug which are given as commands to the infusion pumps. This software provides the anesthesiologist with a trustworthy tool for managing a safe and balanced anesthesia. Since it also incorporates the acquisition and display of patients brain signals.