Validation of an inverse dynamics method to predict joint kinetics in the absence of dynamometry. - Barden, John M. (University of Ottawa (Canada), 1993)
When investigating the joint kinetics of human locomotion, ground reaction forces are typically measured directly using a force platform. In many different skills and movement environments, the utilization of a force platform to collect external force data is not possible. These particular movement situations require an indirect method to estimate joint kinetic variables if they are to be analyzed. This study investigated whether or not an eleven segment, complete body model could be used to accurately predict the net joint reaction forces and moments of force from cinefilm and body segment parameter data, using force platform calculated net joint reaction forces and moments of force as the criterion for validation. The body was modelled as a linked system of pin-connected rigid bodies and was restricted to the sagittal plane analysis of single support locomotions. The movements analyzed for three subjects were jogging, running, the acceleration phase of sprinting, the long jump takeoff and a running front somersault into a forward roll. Displacement and ground reaction force data were both sampled at 100 Hz and low-pass filtered at cutoff frequencies of 6 and 10 Hz, respectively. The film predicted, support limb net joint reaction forces and moments of force were compared to the force platform calculated results using RMSE and Pearson product moment correlation statistics to quantify phase and magnitude variations. It was found that vertical net joint reaction forces can be estimated from displacement data using the inverse dynamics approach and a complete body segment model. Limited success was attained in estimating the horizontal net joint reaction forces. No consistent results were obtained in estimating the net joint moments of force. Further refinements are necessary if net joint moments are to be predicted accurately using this particular method.
Keywords: Engineering, Biomedical.