Estimating sagittal knee and ankle moment during running using only inertial measurement units: a top-down inverse dynamics approach.

Abstract

The net joint moment is a commonly investigated kinetic quantity in running but currently requires force plates and optical motion capture. This study proposes a physics-based top-down inverse dynamics method to estimate net sagittal knee and ankle moment across three speeds using only inertial measurement units (IMUs). This method does not require musculoskeletal modelling, machine learning, pressure insoles, or centre of pressure. The top-down method was validated against a 2D IMU-driven/3D marker-driven OpenSim model and an IMU-based bottom-up inverse dynamics approach. Strong correlations were found for the top-down net sagittal knee (0.87-0.96) and ankle moment (0.83-0.90) during stance. Maximum knee extension moment showed similar values during stance compared to IMU-based references, while maximum ankle plantar flexion moment was significantly higher. The marker-driven OpenSim model showed overall significantly lower values. This study highlights the potential of top-down inverse dynamics in calculating net sagittal knee moment during running using only IMUs, while the sagittal ankle moment was less accurate and needs a different approach. This method could potentially be used for running (i.e. providing feedback) during training sessions. However, a deeper understanding of upper body kinematics and kinetics is needed, as the top-down method is highly dependent on upper body movement.