Estimating Vertical Ground Reaction Force during Running with 3 IMUs

Abstract

Quantification of biomechanical load is crucial to gain insights in the mechanisms causing running related injuries. Ground reaction forces (GRF) can give insights into biomechanical loading, however, measuring GRF is restricted to a gait laboratory. Developments in inertial sensor technology make it possible to measure accelerations outside the lab in the runners’ own environment. Using Newton’s second law, accelerations of body masses can be used to estimate forces. The main objective of this study is to estimate vertical GRF with three inertial measurement units using a generic algorithm based on Newtons second law. This is achieved using a optimization for filtering properties of the acceleration data and body masses. 10 Heel strike runners performed 9 trials at three different velocities (10, 12 and 14km/h) and three different stride frequencies (low, preferred, high), on a instrumented treadmill. Inertial measurement units were placed at sternum, pelvis, upper legs, tibias and feet. Optimization was performed for different sensor configurations. The root mean squared error (RMSE) between the estimated GRF and measured GRF was used as loss function in the optimization. As performance measure of the algorithm, RMSE, active peak error and Pearson’s correlation coefficient were used. The setup with sensors on the tibia and pelvis showed the best result, with an average RMSE of 0.179 bodyweight, peak error of 3. 7% and Pearson’s correlation coefficient of 0.98. Using leave-one-subject-out cross validation, it is shown that the algorithm is generalizable for heel strike runners. Model performance decreases with velocity but increases with stride frequency. The main error of the algorithm is seen in the first 25% of the stance phase, however, the general performance is comparable or better than what is described in current literature.