Innovation of system for early detection of lung injury during mechanical ventilation

Purpose and goal:

The project aimed to develop a real-time monitoring system for lung health during ventilator treatment. Specifically, the goal has been the early detection of acute lung injuries (ARDS), with the potential to reduce mortality and hospitalization days while optimizing healthcare resources. We have developed a model that provides early indications of lung damage, ARDS, through continuous measurement of particle flow in exhaled air. A broader validation is necessary to ensure the effectiveness of the method.

Expected results and effects:

The project´s results demonstrate promising progress towards the development of a real-time monitoring system for lung function during ventilator treatment. Anticipated effects include early detection of lung injuries and enhanced quality of patient care. The project has also contributed to an increased understanding of the correlation between the development of acute lung injury and changes in the number of particles exhaled during ventilator treatment.

In the next step towards a commercial product, a larger study will be conducted to validate the method. Approach and implementation:

The developed method is based on data derived from both human and animal models collected at Lund University. Exhaled particle data is acquired and analyzed using a novel instrument developed by PExA. The collected data has been examined utilizing machine learning by FCC.

Collaboration with Intensive Care Unit specialists has ensured user-friendliness and alignment with specific needs. This interdisciplinary exchange has contributed to an enhanced comprehension of the relationship between particle data and the development of acute airway injury during ventilator treatment.