Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis

| 2021

Foot contact detection through pressure insoles for the estimation of external forces and moments: application to running and walking

In motion analysis studies, classical inverse dynamics
methods require knowledge of the ground reaction forces and
moments (GRF&M) to compute internal forces. Force
platforms are considered as the gold standard to measure
GRF&M applied to the feet. Such devices reduce the
ecological aspect of the experimental conditions by limiting
the analysis area. Estimating external forces from motion data
and dynamic equations circumvents this limitation at the
expense of accuracy.
In such an estimation method, the inverse dynamics problem
is undetermined since contact is modelled by multiple points
representing the potential ground-foot contact area. The
contact is systematically multiple during double support
phases and using multi-point models that Dorn T. W. et al.
(2010) recommends. An optimization approach distributes the
forces preserving the global equilibrium on the active contact
points according to physiological assumptions, e.g.
minimizing external forces. A contact point is considered
active when that point on the foot is in contact with the
ground. Contact detection is usually based on kinematic
parameters such as height and velocity thresholds. Fritz et al.
(2019) showed that the tuning of those parameters according
to the subject and the task affects the accuracy of the method.
Obtaining the correct setting remains time-consuming and
requires biomechanical knowledge to be effective.
This abstract presents a study that evaluates the potential of
pressure insoles to detect contact in an external force
estimation method. Two contact detection methods are
evaluated: one is based on kinematic thresholds and the other
is based on pressure insole data. The evaluation method
consists of comparing the GRF&M estimated by both
methods with those measured by the force platforms during
running and walking.


prediction, ground reaction force


Pauline Morin, Antoine Muller, Charles Pontonnier, Georges Dumont

Institution / Department

Université de Rennes, CNRS, Inria, IRISA

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