Comparison of explicit finite element and mechanical simulation of the proximal femur during dynamic drop-tower testing

• Published in: Journal of biomechanics Vol. 48; no. 2; pp. 224 - 232
• Main Authors: Ariza, O, Gilchrist, S, Widmer, R.P, Guy, P, Ferguson, S.J, Cripton, P.A, Helgason, B
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 21.01.2015; Elsevier Limited
• Subjects: Aged; Aged, 80 and over; Biomechanical Phenomena; Biomechanics; Bone; Bone Density; Bones; Computer simulation; Correlation; Drop tower; Energy Metabolism; Female; Femur; Femur - metabolism; Femur - physiology; Finite Element Analysis; Finite element method; Fracture; Fracture mechanics; Fractures; Humans; Male; Materials Testing; Mathematical analysis; Mathematical models; Mechanical Phenomena; Mechanical properties; Metabolic disorders; Middle Aged; Models, Biological; Osteoporosis; Physical Medicine and Rehabilitation; Stress, Mechanical; Studies; Osteoporosis; Drop tower; Femur; Fracture; Finite element analysis; Bone
• ISSN: 0021-9290; 1873-2380
• DOI: 10.1016/j.jbiomech.2014.11.042

Abstract Current screening techniques based on areal bone mineral density (aBMD) measurements are unable to identify the majority of people who sustain hip fractures. Biomechanical examination of such events may help determine what predisposes a hip to be susceptible to fracture. Recently, drop-tower simulations of in-vitro sideways falls have allowed the study of the mechanical response of the proximal human femur at realistic impact speeds. This technique has created an opportunity to validate explicit finite element (FE) models against dynamic test data. This study compared the outcomes of 15 human femoral specimens fractured using a drop tower with complementary specimen-specific explicit FE analysis. Correlation coefficient and root mean square error (RMSE) were found to be moderate for whole bone stiffness comparison ( R2 =0.3476 and 22.85% respectively). No correlation was found between experimentally and computationally predicted peak force, however, energy absorption comparison produced moderate correlation and RMSE ( R2 =0.4781 and 29.14% respectively). By comparing predicted strain maps to high speed video data we demonstrated the ability of the FE models to detect vulnerable portions of the bones. Based on our observations, we conclude that there exists a need to extend the current apparent level material models for bone to cover higher strain rates than previously tested experimentally.