Development of a Simulation Software Algorithm for High-End Mechanical Ventilators with Functionalities to attend...

Area of Science:

• Biomedical Engineering
• Respiratory Physiology
• Computational Modeling

Background:

• The COVID-19 pandemic has led to a surge in patients requiring mechanical ventilation, particularly in Peru.
• Over 20% of hospitalized COVID-19 patients require mechanical ventilation, highlighting the need for advanced respiratory support.
• Existing mechanical ventilator prototypes offer high-end capabilities, necessitating optimized control algorithms.

Purpose of the Study:

• To design and simulate a pressure-controlled pulmonary ventilation algorithm for mechanical ventilators.
• To evaluate the algorithm's performance under various clinical scenarios and parameter variations.
• To provide a tool for better understanding and clinical diagnosis in respiratory disease management, including COVID-19.

Main Methods:

• Development of a functional design for a pressure-controlled ventilation algorithm.
• Utilization of a linear multi-compartment mathematical model to simulate the human respiratory system.
• Simulation of the algorithm's performance across diverse ventilator and pulmonary parameter settings.

Main Results:

• The algorithm demonstrated adequate responses across multiple simulated scenarios.
• Encouraging results were observed in the mechanical ventilator simulation, validating the algorithm's efficacy.
• The model effectively simulated variations in ventilator and pulmonary parameters.

Conclusions:

• The developed algorithm shows significant potential for enhancing mechanical ventilator functionality.
• This technology can improve clinical diagnosis and treatment strategies for respiratory diseases, including COVID-19 variants and outbreaks.
• Further research and clinical validation are warranted to integrate this algorithm into healthcare settings.