Computationally Efficient Modelling of Proprioceptive Signals in the Upper Limb for Prostheses: a Simulation Study
Author(s)
Williams, I
Constandinou, TG
Type
Journal Article
Abstract
Accurate models of proprioceptive neural patterns could one day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimisation) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modelling. This paper uses and proposes a number of approximations and optimisations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed.
Date Issued
2014-06-09
Citation
Frontiers in Neuroscience, 2014, 8 (181), pp.1-13
ISSN
1662-4548
Publisher
Frontiers
Start Page
1
End Page
13
Journal / Book Title
Frontiers in Neuroscience
Volume
8
Issue
181
Copyright Statement
© 2014 Williams and Constandinou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or
reproduction is permitted which does not comply with these terms.
reproduction is permitted which does not comply with these terms.
License URL
Description
4/09/14 meb. OA paper ok to add
Identifier
http://www.ncbi.nlm.nih.gov/pubmed/25009463
Publication Status
Published
Coverage Spatial
Switzerland