Abstract
Direct in-vivo measurement of individual muscle force requires placement of a force sensing element in series with the musculo-tendon structures, which is infeasible due to the invasive nature of such a procedure. Current non-invasive methods for measuring muscle forces use measurements of muscle activity to estimate force. These estimations are, however, prone to inaccuracies, as muscle activity is not always measurable for the complete set of muscles acting around the joints of interest.
In this paper, we present a novel estimator that integrates a forward dynamics estimation approach with knowledge of the optimal contraction strategy to obtain accurate estimates of individual muscle force when measurement of muscle activity is not available for all muscles. We show that the system improves accuracy over standard estimation methods.
We acknowledge support from the University of Delaware Research Foundation grant no. 16A01402, and from startup funds by the University of Delaware.
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Zonnino, A., Sergi, F. (2019). Model-Based Estimation of Individual Muscle Force Given an Incomplete Set of Muscle Activity Measurements. In: Masia, L., Micera, S., Akay, M., Pons, J. (eds) Converging Clinical and Engineering Research on Neurorehabilitation III. ICNR 2018. Biosystems & Biorobotics, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-030-01845-0_160
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DOI: https://doi.org/10.1007/978-3-030-01845-0_160
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