Title :
Pressure- and Work-Limited Neuroadaptive Control for Mechanical Ventilation of Critical Care Patients
Author :
Volyanskyy, Konstantin Y. ; Haddad, Wassim M. ; Bailey, James M.
Author_Institution :
Sch. of Aerosp. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fDate :
4/1/2011 12:00:00 AM
Abstract :
In this paper, we develop a neuroadaptive control architecture to control lung volume and minute ventilation with input pressure constraints that also accounts for spontaneous breathing by the patient. Specifically, we develop a pressure - and work-limited neuroadaptive controller for mechanical ventilation based on a nonlinear multicompartmental lung model. The control framework does not rely on any averaged data and is designed to automatically adjust the input pressure to the patient´s physiological characteristics capturing lung resistance and compliance modeling uncertainty. Moreover, the controller accounts for input pressure constraints as well as work of breathing constraints. Finally, the effect of spontaneous breathing is incorporated within the lung model and the control framework.
Keywords :
adaptive control; lung; neurocontrollers; patient care; pneumodynamics; pressure control; critical patient care; lung volume control; mechanical ventilation; nonlinear multicompartmental lung model; patient physiology; pressure-limited neuroadaptive control; work-limited neuroadaptive control; Actuators; Adaptation model; Artificial neural networks; Blood; Lungs; Output feedback; Ventilation; Compartmental systems; mechanical ventilation; multicompartment lung model; neuroadaptive control; pressure-limited ventilation; work-limited ventilation; Adaptation, Physiological; Critical Care; Feedback, Physiological; Humans; Lung; Mathematics; Models, Biological; Positive-Pressure Respiration; Pressure; Respiration, Artificial; Tidal Volume; Work of Breathing;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2011.2109963