RESUMO
The presented work relates to the procedure followed for the automation of a portable extracorporeal circulatory support system. Such a device may help increase the chances of survival after suffering from cardiogenic shock outside the hospital, additionally a controller can provide of optimal organ perfusion, while reducing the workload of the operator. Animal experiments were carried out for the acquisition of haemodynamic behaviour of the body under extracorporeal circulation. A mathematical model was constructed based on the experimental data, including a cardiovascular model, gas exchange and the administration of medication. As the base of the controller fuzzy logic was used allowing the easy integration of knowledge from trained perfusionists, an adaptive mechanism was included to adapt to the patient's individual response. Initial simulations show the effectiveness of the controller and the improvements of perfusion after adaptation.
Assuntos
Automação , Circulação Extracorpórea/métodos , Lógica Fuzzy , Algoritmos , Assistência Ambulatorial , Animais , Fármacos Cardiovasculares/administração & dosagem , Simulação por Computador , Eletrocardiografia , Circulação Extracorpórea/instrumentação , Frequência Cardíaca/fisiologia , Hemodinâmica/fisiologia , Humanos , Modelos Cardiovasculares , Troca Gasosa Pulmonar/fisiologia , Choque Cardiogênico/fisiopatologia , Choque Cardiogênico/terapia , Sus scrofaRESUMO
For patients suffering from cardiogenic shock cardiopulmonary resuscitation may not be sufficient to restore normal heart function. However, their chances of survival may be increased with the use of an extracorporeal support system. With this system the patient's organs are perfused while being transported to the nearest hospital for proper treatment. In the automation of an extracorporeal support system the patient's vital signals are constantly monitored and proper adjustments are performed to improve organ perfusion. In this paper, an adaptive fuzzy controller is proposed that uses the knowledge and expertise of a perfusionist as a starting point and reference for regulation. Furthermore it is able to adapt to the patient's specific reactions by manipulating the rule base of the fuzzy controller. The performance of the adaptive fuzzy controller is tested with a simulation model of the cardiovascular system.