Predictive adaptive control of neuromuscular relaxation

This paper explores the application of a multi-step predictive adaptive controller to control the level of neuromuscular relaxation during a general anaesthesia. The problem of neuromuscular relaxation in humans is characterized by a large variability of the pharmacokinetics (PK) and pharmacodynamics (PD) among patients. Because the administrating potent drugs may cause side effects it is important to obtain the adequate level of neuromuscular blockade but avoiding the administration of drug overdoses. To tackle the problem of the variability among patients, the data obtained with the response to the first bolus can be analyzed to extract information of the patient/drug pharmacokinetics/pharmacodynamics. However this approach does not provide a complete solution for the problem, therefore an online model identification based on a nonlinear transformation is explored with the multi-step predictive adaptive controller. Computer simulations are used to evaluate the performance and the main difficulties of its applicability.