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An algorithm for estimation of shoulder muscle forces for clinical use

FAVRE P; SHEIKH R; FUCENTESE SF; JACOB HAC
CLIN BIOMECH , 2005, vol. 20, n° 8, p. 822-833
Doc n°: 121619
Localisation : Documentation IRR
Descripteurs : DD32 - EXPLORATION EXAMENS BILANS - EPAULE

The shoulder joint represents an indeterminate mechanical system, making it difficult to predict individual muscle forces required to equilibrate a given arbitrary external force. Although considerable work has been published on this matter, no model exhibits the adaptability required for the analysis involving different positions of the humerus and for any external load. An algorithm involving decision-making loops is developed to predict forces exerted by muscles that cross the shoulder joint in equilibrating a given external force acting in an arbitrary direction, with the humerus in any one of 12 selected positions. Methods. Muscle lever arms and directions of action collected from a full-size epoxy model of the shoulder joint are used together with the external force as input. The algorithm selects an appropriate group of muscles and step by step attributes small force increments to withstand the external moment while aiming at minimising the forces involved. Each muscle force increment is stored after every loop and eventually summed up. Stability of the glenohumeral joint is the final determining factor. Findings. Six worked-out examples show interesting features of probable muscular activity. Muscle segmentation is of paramount importance for spatial control. Although stability can be achieved by increasing the overall rotator cuff activity (co-contraction), this is rarely necessary. Interpretation. The strategy of force sharing among the muscles opens up the possibility to examine the outcome of muscle deficiencies and to investigate causes of joint instability as encountered in clinical practice. Further validation of the model is still needed, but certain clinical observations can be explained. (c) 2005 Elsevier Ltd. All rights reserved.

Langue : ANGLAIS

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