Information Services banner Edinburgh Research Archive The University of Edinburgh crest

Edinburgh Research Archive >
Informatics, School of >
Informatics Publications >

Please use this identifier to cite or link to this item:

View Statistics

Files in This Item:

File Description SizeFormat
VijayakumarS_A Computational Model of Limb.pdf2.03 MBAdobe PDFView/Open
Title: A Computational Model of Limb Impedance Control Based on Principles of Internal Model Uncertainty
Authors: Mitrovic, Djordje
Klanke, Stefan
Osu, Rieko
Kawato, Mitsuo
Vijayakumar, Sethu
Issue Date: Oct-2010
Journal Title: PLoS ONE
Volume: 5
Issue: 10
Page Numbers: e13601
Publisher: PLoS
Abstract: Efficient human motor control is characterized by an extensive use of joint impedance modulation, which is achieved by co-contracting antagonistic muscles in a way that is beneficial to the specific task. While there is much experimental evidence available that the nervous system employs such strategies, no generally-valid computational model of impedance control derived from first principles has been proposed so far. Here we develop a new impedance control model for antagonistic limb systems which is based on a minimization of uncertainties in the internal model predictions. In contrast to previously proposed models, our framework predicts a wide range of impedance control patterns, during stationary and adaptive tasks. This indicates that many well-known impedance control phenomena naturally emerge from the first principles of a stochastic optimization process that minimizes for internal model prediction uncertainties, along with energy and accuracy demands. The insights from this computational model could be used to interpret existing experimental impedance control data from the viewpoint of optimality or could even govern the design of future experiments based on principles of internal model uncertainty.
ISSN: 1932-6203
Appears in Collections:Informatics Publications

Items in ERA are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh 2013, and/or the original authors. Privacy and Cookies Policy