Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Nov 16;43(15):3007-14.
doi: 10.1016/j.jbiomech.2010.06.015. Epub 2010 Jul 22.

Validation of the Delft Shoulder and Elbow Model using in-vivo glenohumeral joint contact forces

Affiliations

Validation of the Delft Shoulder and Elbow Model using in-vivo glenohumeral joint contact forces

A A Nikooyan et al. J Biomech. .

Abstract

The Delft Shoulder and Elbow Model (DSEM), a large-scale musculoskeletal model, is used for the estimation of muscle and joint reaction forces in the shoulder and elbow complex. Although the model has been qualitatively verified using EMG-signals, quantitative validation has until recently not been feasible. The development of an instrumented shoulder endoprosthesis has now made this possible. To this end, motion data, EMG-signals, external forces, and in-vivo glenohumeral joint reaction forces (GH-JRF) were recorded for two patients with an instrumented shoulder hemi-arthroplasty, during dynamic tasks (including abduction and anteflexion) and force tasks with the arm held in a static position. Motions and external forces served as the model inputs to estimate the GH-JRF. In the modeling process, the effect of two different (stress and energy) optimization cost functions and uniform size and mass scaling were evaluated. The model-estimated GH-JRF followed the in-vivo measured force for dynamic tasks up to about 90° arm elevations, but generally underestimates the peak forces up to 31%; whereas a different behavior (ascending measured but descending estimated force) was found for angles above 90°. For the force tasks the model generally overestimated the peak GH-JRF for most directions (on average up to 34%). Applying the energy cost function improved model predictions for the dynamic anteflexion task (up to 9%) and for the force task (on average up to 23%). Scaling also led to improvement of the model predictions during the dynamic tasks (up to 26%), but had a negligible effect (<2%) on the force task results. Although results indicated a reasonable compatibility between model and measured data, adjustments will be necessary to individualize the generic model with the patient-specific characteristics.

PubMed Disclaimer

Publication types

LinkOut - more resources