Improving a fuzzy logic based weaning algorithm for the patient

Ventilator is a machine that perfoms artificial respiration to person whose respiration has been disturbed. The process of that is called as ventilation. The scientists have made many studies to improve features of this device. At nineties, controlling of this device was implemented with classical control, in recent years, controlling of that has been implemented with artificial intelligence techniques. Currently, patients who have respiratory failure, support with device called as mechanical ventilator (MV). Weaning from mechanical ventilation is important level of mechanical ventilation process that starts with mechanical ventilation. If patients do not need any mechanical ventilation support, this support should be decreased gradually and this process called as weaning from mechanical ventilation. In other words, work of breathing should be transmitted from mechanical ventilator to the patient. But problem of this process is prediction of starting time of weaning from mechanical ventilation. If this process can not be predicted correctly and patient weans early from mechanical ventilation, time delay occurs in this process, and if patient weans lately from mechanical ventilation, time delay occurs again and patient may be addicted to the mechanical ventilator. In this work, existing weaning prediction algorithms were examined and tried to find new alternate method using with Fuzzy Logic, LabVIEW and compared success of this method with other methods. To improving algorithm about weaning from mechanical ventilation, parameters which need to be calculated about patient who have respiratory failure is to be needed. In this work, parameters which need to be calculated about patient who have respiratory failure were generated randomly by using gauss distribution method then given as input to the system which was improved and finally the results were reviewed with expert. Keywords: Ventilator, Mechanical Ventilation, Weaning, LabVIEW, Fuzzy Logic