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Lower back pain is a major public health problem. Despite claims that lumbar belts change spinal posture due to applied pressure on the trunk, no mechanical model has yet been published to prove this treatment. This paper describes a first model for belt design, based on the one hand on the mechanical properties of the fabrics and the belt geometry, and on the other hand on the trunk geometrical and mechanical description. The model provides the estimation of the pressure applied to the trunk, and a unique indicator of the belt mechanical efficiency is proposed: pressure is integrated into a bending moment characterizing the belt delordosing action on the spine. A first in-silico clinical study of belt efficiency for 15 patients with 2 different belts was conducted. Results are very dependent on the body shape: in the case of high BMI patients, the belt effect is significantly decreased, and can be even inverted, increasing the lordosis. The belt stiffness proportionally increases the pressure applied to the trunk, but the influence of the design itself on the bending moment is clearly outlined. Moreover, the belt/trunk interaction, modeled as sticking contact and the specific way patients lock their belts, dramatically modifies the belt action. Finally, even if further developments and tests are still necessary, the model presented in this paper seems suitable for in-silico pre-clinical trials on real body shapes at a design stage. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]