Inverse Dynamics Meets Markerless Motion Capture during Standing: Concurrent Validation of Center of Mass and Center of Pressure Estimations.

Authors

Dorna Nourbakhsh Sabet, Hadi Tamimi, Albert H Vette, Milad Nazarahari

Published in

Annals of biomedical engineering. Aug 01, 2026. Epub Aug 01, 2026.

Abstract

Observational balance assessment is frequently used clinically but remains subjective and limited in accuracy. Although laboratory-based methods provide precise biomechanical measurements, their need for specialized equipment and expertise limits clinical use. This study presents a multi-view, open-source markerless motion capture system (MMCS) using OpenPose to identify body landmarks, enabling objective balance assessment via center-of-mass (COM) and inverse-dynamics-based center-of-pressure (COP) estimation.
The proposed MMCS was experimentally validated. Twelve non-disabled individuals performed five balance tasks (quiet standing on hard and soft surfaces with eyes open and closed, and a weight shift task) against marker-based and force plate measurements. This study also investigated the effect of biomechanical modelling (single-, three-, six-, and eight-segment models) on COM and COP estimations.
Using MMCS, COM trajectories estimated from markerless data showed very high agreement with the marker-based gold standard across models (Pearson's correlation coefficient: CC > 0.90). The COP estimated via the eight-segment model and inverse dynamics showed the highest agreement with force plate data (CC = 0.95-0.98; root-mean-square error: RMSE = 2.2-8.5 mm) in the anterior-posterior direction. Across all models, the anterior-posterior direction showed higher correlations than the medial-lateral direction, except for the weight shift task.
Increasing number of segments, improved CC and RMSE across tasks, confirming the value of multi-segment modelling for COM and COP estimation when using MMCS. These findings demonstrate that our MMCS can achieve agreement consistent with laboratory-based systems for balance assessment. By reducing reliance on specialized laboratories while maintaining biomechanical validity, this framework supports balance evaluation in rehabilitation clinics.

PMID:
42542510
Bibliographic data and abstract were imported from PubMed on 02 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.