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System Identification and Neuromuscular Modeling

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Biomechanics and Neural Control of Posture and Movement

Abstract

“System identification” is a term that describes mathematical techniques used to infer the properties of an unknown system from measurements of the system inputs and outputs. Typically, the inputs to the system are controlled by the experimenter, although the only real requirements are that all the inputs and outputs are known and measurable and that the inputs sufficiently excite the system. System identification techniques have been applied to a wide range of problems, this chapter focuses on applications related to the neuromuscular system (i.e., muscle, joint, and limb mechanics) as well as the neural signals that control posture and movement.

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Authors
  1. Robert E. Kearney
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  2. Robert F. Kirsch
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Editors and Affiliations

  1. Biomedical Engineering Department, Marquette University, Milwaukee, WI, 53201, USA

    Jack M. Winters

  2. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA

    Patrick E. Crago

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Kearney, R.E., Kirsch, R.F. (2000). System Identification and Neuromuscular Modeling. In: Winters, J.M., Crago, P.E. (eds) Biomechanics and Neural Control of Posture and Movement. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2104-3_9

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  • DOI: https://doi.org/10.1007/978-1-4612-2104-3_9

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7415-5

  • Online ISBN: 978-1-4612-2104-3

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