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Is maximum isometric muscle stress the same among prime elbow flexors?

Li L, Tong K, Song R, Koo TK

Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.

BACKGROUND: Previous musculoskeletal modeling studies have adopted the assumption of the same maximum isometric muscle stress among the prime elbow flexors. This study aimed at estimating the maximum isometric muscle stress based on subject-specific modeling parameters measured in vivo and validating that assumption. METHODS: Subject-specific musculoskeletal models of the upper limbs of five normal subjects were developed, which incorporated anthropometrically scaled graphics-based geometrical models and Hill-type musculotendon models of the prime elbow flexors. B-mode ultrasound technique was employed to measure the muscle optimal length and pennation angle of each prime elbow flexor, and these architectural parameters were inputted into the model to reduce the number of unknown parameters to be optimized. To allow changes of individual maximum isometric muscle force of the prime elbow flexors, optimizations were conducted by minimizing the root mean square difference between the predicted and measured isometric torque-angle curves. Maximum isometric muscle stress of each prime elbow flexor was estimated by dividing the maximum isometric muscle force with the corresponding physiological cross-sectional area. FINDINGS: Our findings showed that maximum isometric muscle stress among the prime elbow flexors was not significantly different from each other. Thus it appears that it is reasonable to assume the same value for maximum isometric muscle stress for all prime elbow flexors in musculoskeletal modeling studies. INTERPRETATION: Latest medical imaging techniques such as ultrasound for the estimation of musculotendon parameters would provide an alterative method to obtain the muscle architecture parameters noninvasively. The subject-specific musculotendon parameters estimated in this study could be used for developing the neuromusculoskeletal model to predict muscle force and evaluate muscle functions.

Published 22 August 2007 in Clin Biomech (Bristol, Avon), 22(8): 874-83.
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