Control of Respiratory Mechanics with Artificial Neural Networks

Airway pressure control of respiratory mechanics is crucial for ventilated patients. However, respiratory mechanics are nonlinear and are varying considerably amongst individual patients. In addition nonlinear interactions of a number of controls such as PEEP, Vt,fl02 - just to name a few - complicate the situation for the respiratory therapist on intensive care units. In this paper an alternative approach to traditional control methods - a neural network predictive controller - is proposed to establish an adaptive control of the airway pressure according to the individual features of a mechanically ventilated patient. The experimental results show that this approach can make the ventilator output follow the command pressure accurately as well as successfully identify the individual nonlinear respiratory mechanics of severely sick patients.Control of Respiratory Mechanics with Artificial Neural Networks Hui Zhu College of Mechanical & Electric Eng.