The quantification of the visco-elastic properties (resistance (R), inertia (L) and compliance (C)) of the different chest wall compartments (pulmonary rib cage,diaphragmatic rib cage and abdomen) is important to study the status of the passive components of the respiratory system, particularly in selected pathologies. Applying the viscoelastic-electrical analogy to the chest wall, we used an identification method in order to estimate the R, L and C parameters of the different parts of the chest, basing on different models; the input and output measured data were constituted by the volume variations of the different chest wall compartments and by the nasal pressure during controlled intermittent positive pressure ventilation by nasal mask, while the parameters of the system (R, L and C of the different compartments) were to be estimated. Volumes were measured with a new method, recently validated, based on an opto-electronic motion analyzer, able to compute with high accuracy and null invasivity the absolute values and the time variations of the volumes of each of the three compartments. The estimation of the R, L and C parameters has been based on a least-squared criterion, and the minimization has been based on a robustified iterative Gauss-Newton algorithm. The validation of the estimation procedure (fitting) has ben performed computing the percentage root mean square value of the error between the output real data and the output estimated data. The method has been applied to 2 healthy subjects. Also preliminary results have been obtained from 20 subjects affected by neuromuscular diseases (Duchenne Muscular Dystrophy (DMD) and Spinal Muscle Atrophy (SMA)). The results show that: (a) the best-fitting electrical models of the respiratory system are made up by one or three parallel RLC branches supplied by a voltage generator (so considering inertial properties, particularly in the abdominal compartment, and not considering patient/machine connection); (b) there is a significant difference between DMD and SMA groups (the value of resistance and rigidity of the thorax is much higher in SMA patients); (c) the inclusion of the connection patient-ventilator make the models ill-conditioned. We conclude that this method allows a quantitative evaluation of rib cage and abdominal passive characteristics with a good accuracy and through a dynamic measurement and that it could give significant data in physiology and clinics.
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