Abstract
Finite element models of the musculoskeletal system have the possibility of describing the in vivo situation to a greater extent than a single in vitro experimental study ever could. However these models and the assumptions made must be validated before they can be considered truly useful. The object of this study was to validate, using digital image correlation (DIC) and strain gauging, a novel free boundary condition finite element model of the femur.
The femur was treated as a complete musculoskeletal construct without specific fixed restraint acting on the bone. Spring elements with defined force-displacement relationships were used to characterize all muscles and ligaments crossing the hip and knee joints. This model was subjected to a loading condition representing single leg stance. From the developed model muscle, ligament and joint reaction forces were extracted as well as displacement and strain plots. The muscles with the most influence were selected to be represented in the simplified experimental setup.
To validate the finite element model a balanced in vitro experimental set up was designed. The femur was loaded proximally through a construct representative of the pelvis and balanced distally on a construct representing the tibio-femoral joint. Muscles were represented using a cabling system with glued attachments. Strains were recorded using DIC and strain gauging. DIC is an image analysis technique that enables non-contact measurement of strains across surfaces. The resulting strain distributions were compared to the finite element model.
The finite element model produced hip and knee joint reaction forces comparable to in vivo data from instrumented implants. The experimental models produced strain data from both DIC and strain gauging; these were in good agreement with the finite element models. The DIC process was also shown to be a viable method for measuring strain on the surface of the specimen.
In conclusion a novel approach to finite element modeling of the femur was validated, allowing greater confidence for the model to be further developed and used in clinical settings.
