Numerical Model Reduction for the Prediction of Interface Pressure Applied by Compression Bandages on the Lower Leg

Fanette Chassagne (1, 2) , Jérôme Molimard (1, 2) , Reynald Convert (3) , Pascal Giraux (4, 5) , Pierre Badel (1, 2)

1 SAINBIOSE - Santé Ingénierie Biologie Saint-Etienne
2 CIS-ENSMSE - Centre Ingénierie et Santé
3 Thuasne
4 Faculté de Médecine Jacques Lisfranc [Université Saint-Etienne]
5 LIBM - Laboratoire Interuniversitaire de Biologie de la Motricité

Objective: To develop a new method for the prediction of interface pressure applied by medical compression bandages. Methods: A finite element simulation of bandage application was designed, based on patient-specific leg geometries. For personalized interface pressure prediction, a model reduction approach was proposed, which included the parametrization of the leg geometry. Pressure values computed with this reduced model were then confronted to experimental pressure values. Results: The most influencing parameters were found to be the bandage tension, the skin-to-bandage friction coefficient and the leg morphology. Thanks to the model reduction approach, it was possible to compute interface pressure as a linear combination of these parameters. The pressures computed with this reduced model were in agreement with experimental pressure values measured on 66 patients' legs. Conclusion: This methodology helps to predict patient-specific interface pressure applied by compression bandages within a few minutes whereas it would take a few days for the numerical simulation. The results of this method show less bias than Laplace's Law, which is for now the only other method for interface pressure computation.

Mots clés: Finite element simulation; model reduction; compression bandages; interface pressure

Domaines: Biomécanique [physics.med-ph]

Fanette Chassagne, Jérôme Molimard, Reynald Convert, Pascal Giraux, Pierre Badel. Numerical Model Reduction for the Prediction of Interface Pressure Applied by Compression Bandages on the Lower Leg. IEEE Transactions on Biomedical Engineering, 2018, 65 (2), pp.449-457. ⟨10.1109/TBME.2017.2774598⟩. ⟨hal-02318360⟩