Parametric Study of Lumbar Belts in the Case of Low Back Pain: Effect of Patients’ Specific Characteristics

Conference paper


Objective: A numerical 3D model of the human trunk was developed to study the biomechanical effects of lumbar belts used to treat low back pain.

Methods: This model was taken from the trunk radiographies of a person and simplified so as to make a parametric study by various morphological parameters of the patient, characteristic parameters of the lumbar belt and mechanical parameters of body and finally to determine the parameters influencing the effects of low back pain when wearing the lumbar belt. The loading of lumbar belt is modelled by Laplace’s law. These results were compared with clinical study.

Results: All the results of this parametric study showed that the choice of belt is very important depending on the patient’s morphology. Surprisingly, the therapeutic treatment is not influenced by the mechanical characteristics of the body structures except the mechanical properties of intervertebral discs.

Discussion: The numerical model can serve as a basis for more in-depth studies concerning the analysis of efficiency of lumbar belts in low back pain. In order to study the impact of the belt’s architecture, the pressure applied to the trunk modelled by Laplace’s law could be improved. This model could also be used as the basis for a study of the impact of the belt over a period of wearing time. Indeed, the clinical study shows that movement has an important impact on the distribution of pressure applied by the belt.


Medical device Articular contention Lumbar belt Low back pain Mechanical model 


  1. 1.
    Stucki RF, Waldburger M (2001) Approche multidisciplinaire de la lombalgie commune subaiguë et chronique: expérience suisse romande. Rev Rhum 68(2):178–184Google Scholar
  2. 2.
    Calmels P, Queneau P, Hamonet C et al (2009) Effectiveness of a lumbar belt in subacute low back pain: an open, multicentric, and randomized clinical study. Spine 34(3):215–220Google Scholar
  3. 3.
    Axelsson P, Johnsson R, Strömqvist B (1992) Effect of lumbar orthosis on intervertebral mobility. A roentgen stereophotogrammetric analysis. Spine 17(6):678–681Google Scholar
  4. 4.
    Calmels P, Fayolle-Minon I (1996) An update on orthotic devices for the lumbar spine based on a review of the literature. Rev Rhum 63(4):285–291Google Scholar
  5. 5.
    Fidler MW, Plasmans CM (1983) The effect of four types of support on the segmental mobility of the lumbosacral spine. J Bone Joint Surg 65(7):943–947Google Scholar
  6. 6.
    Andersson BJ, Ortengren R (1974) Lumbar disc pressure and myoelectric back muscle activity during sitting. 3. Studies on a wheelchair. Scand J Rehabil Med 6(3):122–127Google Scholar
  7. 7.
    McGill SM, Norman RW, Sharratt MT (1990) The effect of an abdominal belt on trunk muscle activity and intra-abdominal pressure during squat lifts. Ergonomics 33(2):147–160Google Scholar
  8. 8.
    Nachemson A, Morris JM (1964) In vivo measurements of intradiscal pressure. J Bone Joint Surg 46(5):1077–1092Google Scholar
  9. 9.
    Cholewicki J, Shah KR, McGill KC (2006) The effects of a 3-week use of lumbosacral orthoses on proprioception in the lumbar spine. J Orthop Sports Phys Ther 36(4):225–231Google Scholar
  10. 10.
    Dalichau S, Scheele K (2000) Auswirkungen elastischer lumbal-stützgurte auf den effect eines muskeltrainingsprogrammes für patienten mit chronischen rückenschmerzen. Z Orthop 138(1):8–16Google Scholar
  11. 11.
    Thoumie P, Drape JL, Aymard C et al (1998) Effects of a lumbar support on spine posture and motion assessed by electrogoniometer and continuous recording. Clin Biomech 13(1):18–26Google Scholar
  12. 12.
    Fayolle-Minon I, Calmels P (2008) Effect of wearing a lumbar orthosis on trunk muscles: study of the muscle strength after 21days of use on healthy subjects. Joint Bone Spine 75(1):58–63Google Scholar
  13. 13.
    Kawaguchi Y, Gejo R, Kanamori M et al (2002) Quantitative analysis of the effect of lumbar orthosis on trunk muscle strength and muscle activity in normal subjects. J Orthop Sci 7(4):483–489Google Scholar
  14. 14.
    Reyna JR, Leggett SH, Kenney K et al (1995) The effect of lumbar belts on isolated lumbar muscle. Strength and dynamic capacity. Spine 20(1):68–73Google Scholar
  15. 15.
    Warren LP, Appling S, Oladehin A, Griffin J et al (2001) Effect of soft lumbar support belt on abdominal oblique muscle activity in nonimpaired adults during squat lifting. J Orthop Sports Phys Ther 31(6):316–323Google Scholar
  16. 16.
    Holmström E, Moritz U (1992) Effects of lumbar belts on trunk muscle strength and endurance: a follow-up study of construction workers. J Spinal Disord 5(3):260–266Google Scholar
  17. 17.
    Million R, Nilsen KH, Jayson MI et al (1981) Evaluation of low back pain and assessment of lumbar corsets with and without back supports. Ann Rheum Dis 40(5):449–454Google Scholar
  18. 18.
    Valle-Jones JC, Walsh H, O’Hara J et al (1992) Controlled trial of a back support (‘Lumbotrain’) in patients with non-specific low back pain. Curr Med Res Opin 12(9):604–613Google Scholar
  19. 19.
    Willner S (1985) Effect of a rigid brace on back pain. Acta Orthop Scand 56(1):40–42Google Scholar
  20. 20.
    Carrier J, Aubin CE, Villemure I, Labelle H et al (2004) Biomechanical modelling of growth modulation following rib shortening or lengthening in adolescent idiopathic scoliosis. Med Biol Eng Comput 42(4):541–548Google Scholar
  21. 21.
    Nagasao T, Noguchi M, Miyamoto J et al (2010) Dynamic effects of the Nuss procedure on the spine in asymmetric pectus excavatum. J Thorac Cardiovasc Surg 140(6):1294–1299Google Scholar
  22. 22.
    Pankoke S, Hofmann J, Wölfel HP (2001) Determination of vibration-related spinal loads by numerical simulation. Clin Biomech 16:S45–S56Google Scholar
  23. 23.
    Huynh AM, Aubin CE, Mathieu PA et al (2007) Simulation of progressive spinal deformities in Duchenne muscular dystrophy using a biomechanical model integrating muscles and vertebral growth modulation. Clin Biomech 22(4):392–399Google Scholar
  24. 24.
    Lafortune P, Aubin CE, Boulanger H et al (2007) Biomechanical simulations of the scoliotic deformation process in the pinealectomized chicken: a preliminary study. Scoliosis 2(1):16Google Scholar
  25. 25.
    Villemure I, Aubin CE, Dansereau J et al (2004) Biomechanical simulations of the spine deformation process in adolescent idiopathic scoliosis from different pathogenesis hypotheses. Eur Spine J 13(1):83–90Google Scholar
  26. 26.
    Arjmand N, Plamondon A, Shirazi-Adl A et al (2012) Predictive equations for lumbar spine loads in load-dependent asymmetric one-and two-handed lifting activities. Clin Biomech 27(6):537–544Google Scholar
  27. 27.
    Bazrgari B, Nussbaum MA, Madigan ML et al (2011) Soft tissue wobbling affects trunk dynamic response in sudden perturbations. J Biomech 44(3):547–551Google Scholar
  28. 28.
    Clin J, Aubin CE, Labelle H (2007) Virtual prototyping of a brace design for the correction of scoliotic deformities. Med Biol Eng Comput 45(5):467–473Google Scholar
  29. 29.
    Chagnon A, Aubin CE, Villemure I (2010) Biomechanical influence of disk properties on the load transfer of healthy and degenerated disks using a poroelastic finite element model. J Biomech Eng 132:111006. CrossRefGoogle Scholar
  30. 30.
    Dubuis L, Avril S, Debayle J et al (2012) Patient-specific numerical model of soft tissues in the compressed leg: application to six subjects. Comput Methods Biomech Biomed Engin 15(S1):44–45Google Scholar
  31. 31.
    Bonnaire R (2015) Caractérisation mécanique des orthèses: application aux ceintures de soutien lombaire dans le cadre de la lombalgie. PhD Thesis, Ecole des Mines de Saint-Etienne, FranceGoogle Scholar
  32. 32.
    Bonnaire R, Verhaeghe M, Molimard J et al (2014) Characterization of a pressure measuring system for the evaluation of medical devices. J Eng Med 228:1264–1274Google Scholar
  33. 33.
    Goel VK, Kong W, Han JS et al (1993) A combined finite element and optimization investigation of lumbar spine mechanics with and without muscles. Spine 18(11):1531–1541Google Scholar
  34. 34.
    Périé D, Aubin CE, Lacroix M et al (2004) Biomechanical modelling of orthotic treatment of the scoliotic spine including a detailed representation of the brace-torso interface. Med Biol Eng Comput 42(3):339–344Google Scholar
  35. 35.
    Sylvestre PL, Villemure I, Aubin CE (2007) Finite element modeling of the growth plate in a detailed spine model. Med Biol Eng Comput 45(10):977–988Google Scholar
  36. 36.
    Wagnac E, Arnoux PJ, Garo A et al (2012) Finite element analysis of the influence of loading rate on a model of the full lumbar spine under dynamic loading conditions. Med Biol Eng Comput 50(9):903–915Google Scholar
  37. 37.
    Dreischarf M, Rohlmann A, Bergmann G et al (2011) Optimised loads for the simulation of axial rotation in the lumbar spine. J Biomech 44(12):2323–2327Google Scholar
  38. 38.
    Dreischarf M, Rohlmann A, Bergmann G et al (2010) A non-optimized follower load path may cause considerable intervertebral rotations. J Biomech 43(13):2625–2628Google Scholar
  39. 39.
    Munoz F (2014) Évaluation biomécanique des orthèses lombaires - application à l’orthèse Lordactiv®. PhD Thesis, Univ Jean Monnet, FranceGoogle Scholar
  40. 40.
    Pierrat B, Molimard J, Navarro L et al (2015) Evaluation of the mechanical efficiency of knee braces based on computational modelling. Comput Methods Biomech Biomed Engin 18(6):646–661Google Scholar
  41. 41.
    Malik K, Joseph NJ (2007) Intervertebral disc a source of pain? low back pain: problems and future directions. Middle East J Anaesthesiol 19(3):683–692Google Scholar
  42. 42.
    Poiraudeau S, Lefevre Colau MM, Fayad F et al (2004) Lombalgies. EMC-Rhumatol-Orthop 1(4):295–319Google Scholar
  43. 43.
    Preuss R, Fung J (2005) Can acute low back pain result from segmental spinal buckling during sub-maximal activities? Man Ther 10(1):14–20Google Scholar
  44. 44.
    Turgut AT, Sönmez I, Çakıt BD et al (2008) Pineal gland calcification, lumbar intervertebral disc degeneration and abdominal aorta calcifying atherosclerosis correlate in low back pain subjects: a cross-sectional observational CT study. Pathophysiology 15(1):31–39Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institut Clément Ader (ICA), Université de Toulouse, CNRS, IMT Mines Albi, INSA, ISAESUPAERO, UPSAlbiFrance
  2. 2.Campus JarlardAlbiFrance
  3. 3.Mines Saint-Etienne, Université Jean Monnet, INSERM, UMR1059, SAINBIOSE, CIS-EMSESaint-EtienneFrance
  4. 4.Laboratory of Exercise Physiology (LPE EA4338)University Hospital of Saint-Etienne, Hôpital BellevueSaint-EtienneFrance
  5. 5.ThuasneSaint-EtienneFrance

Personalised recommendations