A robust machine learning enabled decomposition of shear ground reaction forces during the double contact phase of walking

Gait & Posture
Guillaume J BastienMassimo Penta

Abstract

Dynamic analyses of walking rely on the 3D ground reaction forces (GRF) under each foot, while only the resultant force of both limbs may be recorded on a single-belt instrumented treadmill or when both feet touch the same force platform. This study aims to develop a robust decomposition of the shear GRF to complete the most accurate decomposition of the vertical GRF [8]. A retrospective study of 374 healthy adults records (age: 22.8 ± 2.6 years, speed: 1.34 ± 0.28 m/s) and of 434 patient records (age: 21.3 ± 17.8 years, speed: 0.64 ± 0.19 m/s) were used in a machine learning process to develop a robust predictive model to decompose the fore-aft GRF. The lateral GRF was decomposed by resolving the equilibrium of transverse moments around the center of pressure. A predictive linear model of the fore-aft GRF under the back foot every 5% of the double contact phase was obtained from 2 predictors: the total fore-aft GRF and the vertical GRF under the back foot. Each predictor uses a time series of 31 samples before and during the double contact. The model performs accurately in healthy (median[IQR] error of 3.0[2.2-4.1]%) and in clinical gaits (7.7[4.7-13.4]%). The error in lateral GRF decomposition is of 5.7[3.9-10.2]% in healthy ...Continue Reading

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