Computational modelling of bone fracture healing under partial weight-bearing exercise.

Abstract

A great deal of evidence suggests that partial weight-bearing exercise plays an important role in bone fracture healing. However, current physiotherapy program tends to follow the "Let's try it and see" strategy due to the lack of a fundamental understanding of in vivo mechanical environment required for the better healing outcomes. The purpose of present study is to develop an innovative framework to predict the healing outcomes as a result of post-surgical physical therapy. The raw acceleration data corresponding to a series of walking tests is firstly captured by ActiGraph accelerometers, and then used as input to theoretically estimate the peak ground reaction force (PGRF) and peak loading rate (PLR). Finally, the healing outcomes as a result of different walking speeds are predicated based on the interfragmentary movement (IFM) measured by using mechanical testing. The results show that PGRF and PLR are important factors for the callus tissue differentiation at the early stage of healing. The developed model could potentially allow the design of effective patient specific post-surgical physical therapy.