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
über den Boden abrollt. 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.

Schlagwörter

prediction, ground reaction force

Autoren
Institution / Department

Université de Rennes, CNRS, Inria, IRISA

Wir haben Dein Interesse geweckt?

moticon-rego-sensor-insoles-opengo-rego

Sei immer einen Schritt voraus!

Folge uns auf LinkedIn

Und abonniere unseren Newsletter, um die neuesten Informationen über Fallstudien, Produkt-Updates und Unternehmensnachrichten zu erhalten.

Select your desired system

The cutting edge test based outcome assessment system for health professionals and trainers

The most versatile toolkit for free data acquisition and comprehensive analytics in research

Have a general inquiry?

Write us a message for general questions about products and solutions or if you’d like to discuss other topics.


Wähle Deine Produktelinie

Mobile Ganganalysen und sportmotorische Tests für Trainer und Therapeuten – objektiv und effizient.

Das flexible System für freie Datenerfassung und fortgeschrittene Analysen in der Forschung.

Du möchtest eine Anfrage stellen?

Schreibe uns eine Nachricht zu allgemeinen Fragen über Produkte oder zu anwendungsbezogenen Themen, die Du besprechen möchtest.


Das Formular wurde erfolgreich gesendet.

Wir werden uns in Kürze mit dir in Verbindung setzen.

moticon-rego-sensor-insole-live-event

Immer einen Schritt voraus!

Abonniere unseren Newsletter für die neuesten Informationen zu Fallstudien, Webinaren, Produkt-Updates und Neuigkeiten bei Moticon

Hole dir Unterstützung

Finde Antworten zu den häufigsten Fragen in unseren FAQ

Beschreibe Dein Problem so detailliert wie möglich. Hänge Screenshots oder Daten an, sofern das hilfreich ist.


Need help?
Want a live demo?
Interested in prices?
Want to say hello?
Always just a call away
+49 89 2000 301 60
Du brauchst Unterstützung?
Du möchtest eine Live Demo?
Interessiert an Preisen?
Du hast Fragen?
Nur einen Anruf entfernt
+49 89 2000 301 60

The form was sent successfully.

You will be contacted shortly.

Get support

Check our FAQ database for answers to frequently asked questions

Describe your issue in as much detail as possible. Include screenshots or files if applicable.