Interview with the Development Team of alveo

Interview with Mattias van der Staay (CTO, IMT) and Harri Friberg (CEO, IMT Analytics) about the development of the alveo Lung Simulator.

To better understand what led to the decision to develop an advanced lung simulator, we spoke with Matthias van der Staay, Chief Technical Officer of IMT, and Harri Friberg, CEO of IMT Analytics, about the challenges and technical intricacies involved in engineering a vital component for training and engineering purposes.

What inspired the development of alveo as a new lung simulator concept?

Harri Friberg: Traditional lung simulators have limitations in replicating the complex behavior of human lungs, especially under dynamic conditions. We recognized a need for a more realistic, adaptive, high-fidelity simulator that mimics lung mechanics realistically. Moreover, we were unsatisfied with the current simulators' ability to simulate leak scenarios, especially when engineering ventilators for our customers at imt. Leak compensation is one of the most challenging tasks in developing or improving a ventilator, so a realistic leakage simulation is essential for the ventilator's quality.

How does alveo differentiate itself from existing lung simulators in the market?

Matthias van der Staay: Unlike conventional piston-driven simulators, alveo uses turbine-driven technology to control airflow and compliance precisely. It can also dynamically adjust to different conditions in real time, something traditional concepts struggle with.

What challenges did you face when designing a new approach to lung simulation?

Matthias van der Staay: The biggest challenge was achieving real-time responsiveness while keeping the design compact and efficient. Piston-driven systems have simple linear movement, but turbines need precise control algorithms to simulate lung compliance accurately. We also had to ensure compatibility with ventilator testing and medical training scenarios.

Could you explain the core scientific principles behind alveo and how it more accurately replicates lung behavior?

Harri Friberg: alveo relies on turbine-driven airflow control, which can instantly adapt to lung resistance and compliance changes. It uses advanced sensors and feedback loops to dynamically adjust pressure, tidal volume, and flow rates, providing a more physiological response than piston-driven systems.

_________________________________________________________________________________________________________________________________

Technology and Benefits of Turbine-Driven Simulation

Traditional lung simulators often use piston-driven mechanisms. What limitations do you see in that approach?

Matthias van der Staay: Piston-driven simulators are mechanically rigid, meaning they can’t rapidly adjust to changes in breathing dynamics. They struggle with simulating irregular breathing patterns, like those seen in patients with ARDS or obstructive lung diseases.

What advantages does turbine-driven technology have over piston-driven models?

Matthias van der Staay: Turbines offer real-time adaptability, precise control over airflow, and the ability to replicate patient-specific lung behavior more accurately. They also allow for more compact designs without sacrificing performance. Simulating immediate responsiveness to changes in lung conditions is also better. Turbines replicate patient-specific breathing patterns, including irregular patterns or asynchronies, and precise control over tidal volume, pressure, and flow better than mechanical pistons.

How does alveo handle rapid changes in breathing patterns compared to piston-based systems?

Matthias van der Staay: The simulator continuously monitors airflow and pressure changes, instantly adjusting the turbine’s speed to mimic natural breathing variations—something piston-based models can’t do effectively.

Can the device simulate more complex pulmonary conditions or previously complicated responses with piston-driven simulators?

Harri Friberg: Absolutely. alveo can simulate nearly unlimited variations of lung conditions like ARDS, COPD, and Asthma, even variable lung compliance within the same test, which isn’t feasible with traditional piston-based models.

_________________________________________________________________________________________________________________________________

Opportunities for Ventilator Manufacturers

How can ventilator manufacturers use alveo to improve product development and testing?

Matthias van der Staay: We provide a highly realistic testing environment, allowing ventilator manufacturers to fine-tune their devices under different lung conditions, reducing development time and costs.

In what ways does alveo contribute to improving ventilator algorithms and software development?

Harri Friberg: alveo provides real-time, high-fidelity feedback and realistic leakage scenarios, which helps ventilator companies optimize algorithms for pressure support, volume control, adaptive, and closed-loop ventilation.

_________________________________________________________________________________________________________________________________

Future Potential and Roadmap

Where do you see the future of lung simulation heading, and how does the simulator fit into that vision?

Harri Friberg: The future is in Artificially Intelligence (AI)-driven, patient-specific simulation. This device is the first step toward creating fully adaptive lung models that react dynamically.

Do you have plans to integrate AI or machine learning into alveo?

Matthias van der Staay: With the release, we’re already offering a fully adaptive physiologic feedback model and constantly working on improving it for more realistic scenarios. AI will play an essential role in this process, helping ventilators to learn and adjust dynamically.

Are there any upcoming enhancements or versions of alveo that are in development?

A: We have begun developing an advanced software version that will primarily serve research and ventilator development; dedicated neonatal software is already in preparation. Additionally, we aim to explore the often-overlooked simulation for veterinary purposes, with more to come after the launch later this year.

Thank you, Matthias and Harri, for these interesting insights; we’re looking forward to the launch of alveo!