Prediction of ground reaction forces and moments during sports-related movements

When performing inverse dynamic analysis (IDA) of musculoskeletal models to study human motion, inaccuracies in experimental input data and a mismatch between the model and subject lead to dynamic inconsistency. By predicting the ground reaction forces and moments (GRF&Ms) this inconsistency can be reduced and force plate measurements become unnecessary. In this study, a method for predicting GRF&Ms was validated for an array of sports-related movements. The method was applied to ten healthy subjects performing, for example, running, a side-cut manoeuvre, and vertical jump. Pearson’s correlation coefficient ( $r$ ) and root-mean-square deviation were used to compare the predicted GRF&Ms and associated joint kinetics to the traditional IDA approach, where the GRF&Ms were measured using force plates. The main findings were that the method provided estimates comparable to traditional IDA across all movements for vertical GRFs ( $r$ ranging from 0.97 to 0.99, median 0.99), joint flexion moments ( $r$ ranging from 0.79 to 0.98, median 0.93), and resultant joint reaction forces ( $r$ ranging from 0.78 to 0.99, median 0.97). Considering these results, this method can be used instead of force plate measurements, hereby, facilitating IDA in sports science research and enabling complete IDA using motion analysis systems that do not incorporate force plate data.