Which data should be tracked in forward-dynamic optimisation to best predict muscle forces in a pathological co-contraction case?
The choice of the cost-function for predicting muscle forces during a movement remains a challenge, especially in patients with neuromuscular disorders. Forward dynamics-based optimisations mainly track joint kinematics or torques, combined with a least-excitation criterion. Tracking marker trajecto...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
4 January 2018
|
| In: |
Journal of biomechanics
Year: 2018, Jahrgang: 68, Pages: 99-106 |
| ISSN: | 1873-2380 |
| DOI: | 10.1016/j.jbiomech.2017.12.028 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.jbiomech.2017.12.028 Verlag, lizenzpflichtig, Volltext: http://www.sciencedirect.com/science/article/pii/S0021929017307418 
|
| Verfasserangaben: | Colombe Bélaise, Benjamin Michaud, Fabien Dal Maso, Katja Mombaur, Mickaël Begon |
| Zusammenfassung: | The choice of the cost-function for predicting muscle forces during a movement remains a challenge, especially in patients with neuromuscular disorders. Forward dynamics-based optimisations mainly track joint kinematics or torques, combined with a least-excitation criterion. Tracking marker trajectories and/or electromyography (EMG) has rarely been proposed. Our objective was to determine the best tracking objective-function to accurately predict the upper-limb muscle forces. A musculoskeletal model was created and EMG was simulated to obtain a reference movement - a shoulder abduction. A Gaussian noise (mean=0; standard deviation=15%) was added to the simulated EMG. Another noise - corresponding to the actual soft tissue artefacts (STA) of experimental shoulder abduction movements - was added to the trajectories of the markers placed on the model. Muscle forces were estimated from these noisy data, using forward dynamics assisted by six non-linear least-squared objective-functions. These functions involved the tracking of marker trajectories, joint angles or torques, with and without EMG-tracking. All six approaches used the same musculoskeletal model and were solved using a direct multiple shooting algorithm. Finally, the predicted joint angles, muscle forces and activations were compared to the reference values, using root-mean-square errors (RMSe) and biases. The force RMSe of the approach tracking both marker trajectories and EMG (18.45±12.60N) was almost five times lower than the one of the approach tracking only joint angles (82.37±66.26N) or torques (85.10±116.40N). Therefore, using EMG as a complementary tracking-data in forward dynamics seems to be promising for the estimation of muscle forces. |
|---|---|
| Beschreibung: | Gesehen am 11.03.2020 |
| Beschreibung: | Online Resource |
| ISSN: | 1873-2380 |
| DOI: | 10.1016/j.jbiomech.2017.12.028 |