System Identification and Neuromuscular Modeling

  • Robert E. Kearney
  • Robert F. Kirsch
Chapter

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.

Keywords

Joint Stiffness Neuromuscular System Volterra Kernel Functional Expansion Wiener Kernel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag New York, Inc. 2000

Authors and Affiliations

  • Robert E. Kearney
  • Robert F. Kirsch

There are no affiliations available

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