Matemática e Estatística | Comunicações em congressos, conferências e seminários / Communications in congresses, conferences
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Browsing Matemática e Estatística | Comunicações em congressos, conferências e seminários / Communications in congresses, conferences by Author "Amorim, Pedro"
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- ARX modeling of drug effects on brain signals during general anesthesiaPublication . Nunes, Catarina S.; Lobo, Francisco A.; Amorim, PedroThe effect of drugs’ interaction on the brain signal Bispectral Index (BIS) of the EEG, is of great importance for an anesthesia control drug infusion system. In this study, the objective was to investigate if an autoregressive with exogenous inputs model (ARX) could be a suitable approach to predicting BIS according to the anesthetic drugs concentrations. Data were collected in 45 neurosurgeries with total intravenous anesthesia every 5s. A stochastic ARX model was fitted to the data of each patient. The models structure that performed better as predictor used a 30s lag for BIS, 1min lag for propofol and 2min lag for remifentanil. The models had a good performance with statistical zero errors (P < 0.05) in 31 patients. The average of absolute errors was 8.2 ± 2.5, showing that the model captures the brain signal trend. This model proved to be effective in modeling and one step prediction of the BIS signal capturing unique characteristics. The results show that the previous brain response trend has influence on the present value, in addition the drugs concentrations from the previous 2min still have influence. This is an important conclusion for the development of drug infusion controller algorithms.
- Comparison of neural networks, fuzzy and stochastic prediction models for return of consciousness after general anesthesiaPublication . Nunes, Catarina S.; Mendonca, T. F.; Amorim, Pedro; Ferreira, D. A.; Antunes, L.This paper presents three modeling techniques to predict return of consciousness (ROC) after general anesthesia, considering the effect concentration of the anesthetic drug at awakening. First, several clinical variables were statistically analysed to determine their correlation with the awakening concentration. The anesthetic and the analgesic mean dose during surgery, and the age of the patient, proved to have significantly high correlation coefficients. Variables like the mean bispectral index value during surgery, duration of surgery did not present a statistical relation with ROC. Stochastic regression models were built using the variables with higher correlation. Secondly, fuzzy models were built using an Adaptive Network-Based Fuzzy Inference System (ANFIS) also relating different sets of variables. Thirdly, radial basis function (RBF) neural networks were trained relating different sets of clinical values with the anesthetic drug effect concentration at awakening. Clinical data was used to train and test the models. The stochastic models and the fuzzy models proved to have good prediction properties. The RBF network models were more biased towards the training set. The best balanced performance was achieved with the fuzzy models.
- Control of depth of anesthesia using MUSMAR: exploring electromyography and the analgesic dose as accessible disturbancesPublication . Nunes, Catarina S.; Mendonca, Teresa; Lemos, Joao M.; Amorim, PedroThe problem of controlling the level of depth of anesthesia measured by the Bispectral Index (BIS) of the electroencephalogram of patients under general anesthesia, is considered. It is assumed that the manipulated variable is the infusion rate of the hypnotic drug propofol, while the drug remifentanil is also administered for analgesia. Since these two drugs interact, the administration rate of remifentanil is considered as an accessible disturbance in combination with the level of electromyography (EMG) that also interferes with the BIS signal. In order to tackle the high uncertainty present on the system, the predictive adaptive controller MUSMAR is used. The performance of the controller is illustrated by means of simulation with 45 patient individual adjusted models, which incorporate the effect of the drugs interaction on BIS. This controller structure proved to be robust to the EMG and remifentanil disturbances, patient variability, changing reference values and noise.
- EEG signatures at the transition between conscious and unconscious state during induction of general anesthesia with remifentanil and propofolPublication . Ferreira, Ana Isabel Leitão; Mendes, Joaquim; Amorim, Pedro; Nunes, Catarina S.The precise identification of the moment of Loss Of Consciousness (LOC) during the induction phase of general anesthesia is of extreme importance for the individualization of drug doses. In the lack of an objective method to assess this moment, the development of a new methodology is needed. In this observational study, Electroencephalogram (EEG) signatures that were associated with the moment of LOC are examined as a starting point, so as to create a robust model for tracking the dynamic changes between conscious and unconscious states. The data from 12 patients under general anesthesia for neurosurgical procedures with remifentanil and propofol, are used is this study. Multitaper spectrograms were computed to observe the dynamics of EEG oscillations before and after LOC. At LOC, a decrease in gamma power and an increase in delta and alpha bands were identified.
- Hypnotic administration for anesthesia using sliding-mode controlPublication . Castro, Ana; Nunes, Catarina S.; Amorim, Pedro; Almeida, Fernando G.Nowadays general anesthesia is maintained using as the controller the human intervention, relying only on the quick and certain response of the anesthesiologist to the surrounding conditions, in order to provide the adequate state of anesthesia for the three main components - hypnosis, analgesia and paralysis. One of the most advantageous breakthroughs in anesthesia has been the appearance of depth of anesthesia monitors, assisting anesthesiologists in the hard job of knowing the hypnotic state of a patient. This information allows a way of closing the loop for administration of the hypnotic drug, and a more secure maintenance of hypnosis. The objective of this work was to apply sliding-mode control techniques to the model structure of the hypnotic in the human body (measured by the effect), and evaluate the robustness of this method to expected deviations from the average patient.
- Incidence of BIS above 60 during propofol/remifentanil anesthesia for cervical spine surgery and possible awareness comparing standard versus deep neuromuscular blockade with sugammadex reversalPublication . Saúl, R. A. Cardoso; Nunes, Catarina S.; Amorim, Pedro; Seixas, Pedro Francisco Afonso Salgado Amaral
- 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.
- Modeling state entropy of the EEG and auditory evoked potentials: hypnotic and analgesic interactionsPublication . Castro, Ana; Amorim, Pedro; Nunes, Catarina S.Because of the complexity of raw electroencephalogram (EEG), for the anesthesiologist it is very difficult to evaluate the patient’s hypnosis state. Because of this, several depth of anesthesia monitors have been developed, and are in current use at the operating room (OR). These monitors convert the information supplied by the EEG or derived signals into a simple, easy to understand index. Nowadays, general anesthesia is controlled only by the clinician, which decides what is the best drug combination for the patient, regarding all information given by monitors and sensors in the OR. In this work, we collected data from two study groups with auditory evoked potentials (AEP) monitoring, and Entropy (SE) monitoring. A model was fitted to the signals and the Hill equation parameters adjusted, in both study groups. The objective was to predict hypnosis indices, regarding only the drugs administered to a patient, and capture the initial individual patient characteristics that might influence the drugs interaction in the human body. Hypnotic and analgesic drugs interact in different ways throughout the anaesthesia stages. The models obtained captured the different dynamic interaction of drugs, during the induction and maintenance phases, demonstrating that the model must have incorporated all this information in order to perform satisfactorily. Other information like haemodynamic variables might be included in the search for the optimum model.
- A neuro-fuzzy approach for predicting hemodynamic responses during anesthesiaPublication . Amorim, PedroThe effect of drugs’ interaction on the hemodynamic variables is of great importance when considering patient’s safety and stability. It is also important for control infusion systems during anesthesia. In this article, an adaptivenetwork fuzzy inference system is used to model the effect of two drugs (propofol and remifentanil) on the mean arterial pressure and heart rate. The clinical data of 45 patients is used to train and test the model. The use of subtractive clustering improved the model performance on the testing data set. The fuzzy model is able to capture the synergistic interaction between the two drugs, but other influences were detected.
- Neuro-fuzzy models to predict the required propofol amount for loss of consciousness during general anesthesia: a preliminary studyPublication . Ferreira, Ana Isabel Leitão; Mendes, Joaquim; Amorim, Pedro; Nunes, Catarina S.This study presents several models to predict the total amount of the anesthetic drug propofol required to achieve loss of consciousness during the induction phase of anesthesia, considering different clinical variables. The data from 49 patients under anesthesia for neurosurgical procedures, were used in this study. Takagi-Sugeno-Kang (TSK) fuzzy models were used to describe the effect of clinical variables on the amount of propofol required for loss of consciousness. The parameters of the TSK models were optimized using an Adaptive Network-Fuzzy Interference System. All models were trained with the data of 35 patients and tested with the data of 14 patients. These models proved to have reasonable prediction properties. The fuzzy model with the best balanced performance used only two inputs: the systolic arterial pressure and the Bispectral Index of the EEG.