Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Estimation of muscle forces in over-actuated musculoskeletal models involves optimal distributions of net joint moments among muscles by a standard load-sharing scheme (SLS). Given that co-contractions of antagonistic muscles are counterproductive in the net joints moments, SLS might underestimate the co-contractions. Muscle co-contractions play crucial roles in stability of the glenohumeral (GH) joint. The aim of this study was to improve estimations of muscle co-contractions by incorporating electromyography (EMG) data into an upper limb musculoskeletal model. To this end, the model SLS was modified to develop an EMG-assisted load-sharing scheme (EALS). EMG of fifteen muscles were measured during arm flexion and abduction on a healthy subject and fed into the model. EALS was compared to SLS in terms of muscle forces, GH joint reaction force, and a stability ratio defined to quantify the GH joint stability. The results confirmed that EALS estimated higher muscle co-contractions compared to the SLS (e.g., above 50 N higher forces for both triceps long and biceps long during arm flexion).
Alexandre Terrier, Pezhman Eghbalishamsabadi, Matthieu Boubat