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Nonparametric block-structured modeling of lung tissue strip mechanics
G N Maksym1, R E Kearney, J H Bates
1Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada.
Annals of Biomedical Engineering
|April 3, 1998
Summary
A Hammerstein model accurately describes dog lung tissue mechanics, separating static nonlinear behavior from linear dynamics across various conditions. This model offers a robust approach to understanding lung tissue responses.
Area of Science:
- Biomechanics
- Respiratory Physiology
- Nonlinear System Analysis
Background:
- Understanding lung tissue mechanics is crucial for respiratory physiology.
- Lung tissue exhibits complex nonlinear and dynamic behaviors under stress.
- Previous models have limitations in capturing these complex behaviors.
Purpose of the Study:
- To identify and validate a nonlinear model for dog lung tissue.
- To determine if static and dynamic behaviors are separable.
- To assess model performance across different strain amplitudes and stresses.
Main Methods:
- Applied pseudorandom uniaxial perturbations (0.125-12.5 Hz) to dog lung tissue strips.
- Fitted three nonlinear block-structured models: Hammerstein, Wiener, and parallel.
- Evaluated model performance based on stress signal variance and parameter stability.
Main Results:
- Hammerstein and Wiener models explained >99% of stress signal variance.
- Hammerstein model parameters were independent of strain amplitude and mean stress.
- A specific Hammerstein model achieved 99.84% variance accounting, matching quasistatic behavior.
Conclusions:
- The static nonlinear behavior of dog lung tissue is separable from its linear dynamic behavior.
- The Hammerstein model provides a robust and accurate representation of lung tissue mechanics.
- This finding advances the understanding of respiratory system dynamics and modeling.