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Relaxed individual control of skeletal muscle forces via physical human–robot interaction

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Abstract

This study develops a relaxed formulation of a method for controlling individual muscle forces using exoskeleton robots. Past studies have developed a muscle-force control method with very strict limitations on the conditions. These conditions will be removed, and the problem will be reformulated as a constrained optimization of several parameters. The optimization algorithm recognizes when a solution to the muscle control problem cannot be exactly realized, and finds the solution that minimizes the mean errors of the individual muscles between expected and desired muscle activation. This is demonstrated in a computer simulation of human arm dynamics and compared against the prior method to demonstrate its wider applicability. In addition, the control method is extended to resolve issues associated with a nonideal exoskeleton with incomplete torque application to the joints. A quasi-optimized motor-task that minimizes the errors in target muscles and nontarget muscles can be obtained. This paper presents theoretical analysis, simulation, and experimental results on the performance of the relaxed individual muscle control.

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Acknowledgements

This work was supported in part by the National Science Foundation (NSF) under Grant: IIS 1142438 and Japan Science and Technology Agency (JST)—National Science Foundation (NSF) Strategic International Cooperative Program. The authors would like to thank Ellenor Brown for reading the manuscript and for her helpful suggestions.

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Authors and Affiliations

  1. Bio-Robotics and Human Modeling Laboratory, Georgia Institute of Technology, 771 Ferst Drive, Atlanta, GA, 30332-0405, USA

    William Gallagher & Jun Ueda

  2. RIKEN-TRI Collaboration Center for Human-Interactive Robot Research, Advanced Science Institute, RIKEN, 2271-130, Anagahora, Shimoshidami, Moriyama-ku, Nagoya, Aichi, 463-0003, Japan

    Ming Ding

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  1. William Gallagher
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  2. Ming Ding
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  3. Jun Ueda
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Correspondence to William Gallagher.

Appendix: Crowninshield’s Static Optimization

Appendix: Crowninshield’s Static Optimization

Crowninshield’s method [14] is a special case presented in (3) that predicts human muscle forces by minimizing a physiologically based criterion u(f):

(53)

where PCSA j is the physiological cross sectional area (PCSA), and f maxj =ε⋅PCSA j is the maximum muscle force of the j-th muscle. In this paper, \(\varepsilon = 0.7 \times 10^{6}~\mathrm{[N/m^{2}]}\) is given according to [7]. PCSA j ’s are given according to [10]. f minj =0,∀j and r=2 are used. See [14] for the choice of r.

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Gallagher, W., Ding, M. & Ueda, J. Relaxed individual control of skeletal muscle forces via physical human–robot interaction. Multibody Syst Dyn 30, 77–99 (2013). https://doi.org/10.1007/s11044-013-9362-y

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