Parameter Scaling Protocol for Upper-limb Musculoskeletal Models

Master Thesis (2019)
Author(s)

P. Peñas de Santos (TU Delft - Mechanical Engineering)

Contributor(s)

Frans C T van Der Helm – Mentor (TU Delft - Biomechatronics & Human-Machine Control)

M. Mirakhorlo – Graduation committee member (TU Delft - Intelligent Vehicles)

Faculty
Mechanical Engineering
Copyright
© 2019 Pablo Peñas de Santos
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Pablo Peñas de Santos
Graduation Date
31-10-2019
Awarding Institution
Delft University of Technology
Faculty
Mechanical Engineering
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Abstract

Generic musculoskeletal models are not reliable predicting inter-individual variations in muscle forces. Scaling the model parameters is necessary to represent the muscle characteristics of the subjects and thus to pinpoint the differences in force capacity. Optimal Fiber (OFL) and Tendon Slack Length (TSL) have been identified as the two most influential parameters in muscle force generation. The goal of the current study is adjusting a lower-limb scaling algorithm for OFL and TSL to the Delft Shoulder and Elbow Model (DSEM). Furthermore, we evaluate the effect on the preservation of model consistency and muscle force production. Firstly, we scaled the DSEM geometrically. That drove twenty-two muscles to work out of the physiological range in the F-L curve up to 41% of the shoulder ROM. Moreover, the consistency of the model dropped by 78%. We tested three approaches to scale OFL and TSL. The constrained method delivered the best results reducing these percentages to 8% and 2.9%, respectively. It also increased the muscle force production of the DSEM 1.2%BW compared to the geometrically scaled version. The adaptation of the constrained scaling algorithm to the DSEM provides consistency values in the same range observed in lower-limb models. Therefore, we state that it is necessary to scale OFL and TSL whenever the dimensions of the DSEM are modified to obtain reliable muscle force estimations. We recommend further validation of the procedure developed in this article, for example, against data from instrumented endoprosthesis.

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