A new infant hybrid respiratory simulator: preliminary evaluation based on clinical data

Area of Science:

• Biomedical Engineering
• Respiratory Physiology
• Pediatric Critical Care

Background:

• Infant respiratory system mechanics are complex and challenging to model.
• Accurate simulation tools are needed for research and training in neonatal ventilation.

Purpose of the Study:

• To evaluate a novel hybrid (numerical-physical) simulator for infant respiratory system mechanics.
• To assess the simulator's ability to replicate spontaneous and assisted ventilation in various infant populations.

Main Methods:

• Developed a hybrid simulator combining a numerical seven-compartmental model with a physical impedance transformer.
• Integrated LabVIEW real-time software for coordinated operation and ventilator interaction.
• Simulated pressure-controlled ventilation in five groups of "artificial infants" using clinical data.

Main Results:

• The simulator accurately reproduced infant respiratory system mechanics, with no significant differences between simulated and clinical parameters.
• High correlation coefficients were achieved for airway resistance (γR = 0.99), dynamic compliance (γC = 0.85), and work of breathing (γWOB = 0.96).

Conclusions:

• The hybrid simulator effectively reproduces infant respiratory system mechanics.
• This validated tool can aid in understanding and managing respiratory conditions in neonates.