Role of intrinsic muscle properties in producing smooth movements

Andrew M. Krylow, W. Zev Rymer

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

Human upper limb movement trajectories have been shown to be quite smooth, in that time derivatives of end point position (r), including d3r/dt3 (i.e., jerk), appear to be minimized during rapid voluntary reaching tasks. Studies have suggested that these movements are implemented by an optimal neural controller which seeks to minimize a cost function, such as average jerk cost, over the course of these motions. While this hypothetical control strategy is widely supported, there are substantial difficulties associated with implementing such a controller, including ambiguities inherent in transformations from Cartesian to joint coordinates, and the lack of appropriate transducers to provide information about higher derivatives of limb motion to the nervous system. Given these limitations, we evaluate the possibility that smoothing of movement might be induced primarily by the intrinsic mechanical properties of muscle by recording the trajectories of inertially loaded muscle with the excitatory input held constant. These trajectories are compared with those predicted by a minimum- jerk optimization model, and by a Hill-based muscle model. Our results indicate that trajectories produced by inertially loaded muscle alone are smooth (in the minimum-jerk sense), and that muscle properties may suffice to account for much of the observed smoothing of voluntary motion, obviating the need for an optimizing neural strategy.

Original languageEnglish (US)
Pages (from-to)165-176
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Volume44
Issue number2
DOIs
StatePublished - 1997

Keywords

  • Hill's model
  • minimum-jerk
  • muscle modeling
  • muscle properties
  • smoothness

ASJC Scopus subject areas

  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Role of intrinsic muscle properties in producing smooth movements'. Together they form a unique fingerprint.

Cite this