Reconstructing Walking Dynamics From Two Shank-Mounted Inertial Measurement Units

Abstract

Inertial measurement unit (IMU)-based sensing systems have received extensive attention for wearable gait measurement due to their small size, low price, and high accuracy. However, reconstructing walking dynamics usually requires a large number of sensor units attached to major body segments, which is generally not suitable for daily-life scenarios. Previous studies showed that two shank-mounted IMUs can detect gait events and estimate many important gait parameters. However, it is unclear whether this simple two-IMU system can be used to reconstruct walking dynamics. In this article, we propose a two-stage method for predicting walking dynamics from measurements of two shank-mounted IMUs. Displacements of ankle joints and shank angles are first estimated from the IMU outputs. Then, a model-based whole-step optimization approach is used to solve the gait dynamics by tracking the estimated shank motion. The proposed method is validated with both normal and asymmetric walking data, achieving a root-mean-square error of 5.3°, 6.1°, and 6.8° in the hip, knee, and ankle joint angle estimation and 3.9% and 12.2% body weight in the fore-aft and vertical ground reaction force estimation. Comparing with the reported results in the literature, the number of IMUs is significantly reduced with similar accuracy. This implies that gait dynamic information may be estimated from very limited measurements and the inherent gait characteristics can be used to reconstruct gait dynamics from the motion of a small number of segments.