Robotic assessment of neuromuscular characteristics using musculoskeletal models: A pilot study

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dc.contributor.author Jayaneththi, Vinura en
dc.contributor.author Viloria, J en
dc.contributor.author Wiedemann, Lukas en
dc.contributor.author Jarrett, Christopher en
dc.contributor.author McDaid, Andrew en
dc.date.accessioned 2019-06-13T02:02:04Z en
dc.date.issued 2017-07-01 en
dc.identifier.citation Computers in Biology and Medicine 86:82-89 01 Jul 2017 en
dc.identifier.issn 0010-4825 en
dc.identifier.uri http://hdl.handle.net/2292/46979 en
dc.description.abstract Objective: Non-invasive neuromuscular characterization aims to provide greater insight into the effectiveness of existing and emerging rehabilitation therapies by quantifying neuromuscular characteristics relating to force production, muscle viscoelasticity and voluntary neural activation. In this paper, we propose a novel approach to evaluate neuromuscular characteristics, such as muscle fiber stiffness and viscosity, by combining robotic and HD-sEMG measurements with computational musculoskeletal modeling. This pilot study investigates the efficacy of this approach on a healthy population and provides new insight on potential limitations of conventional musculoskeletal models for this application. Methods: Subject-specific neuromuscular characteristics of the biceps and triceps brachii were evaluated using robot-measured kinetics, kinematics and EMG activity as inputs to a musculoskeletal model. Results: Repeatability experiments in five participants revealed large variability within each subjects evaluated characteristics, with almost all experiencing variation greater than 50% of full scale when repeating the same task. Conclusion: The use of robotics and HD-sEMG, in conjunction with musculoskeletal modeling, to quantify neuromuscular characteristics has been explored. Despite the ability to predict joint kinematics with relatively high accuracy, parameter characterization was inconsistent i.e. many parameter combinations gave rise to minimal kinematic error. Significance: The proposed technique is a novel approach for in vivo neuromuscular characterization and is a step towards the realization of objective in-home robot-assisted rehabilitation. Importantly, the results have confirmed the technical (robot and HD-sEMG) feasibility while highlighting the need to develop new musculoskeletal models and optimization techniques capable of achieving consistent results across a range of dynamic tasks. en
dc.relation.ispartofseries Computers in Biology and Medicine en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/ en
dc.title Robotic assessment of neuromuscular characteristics using musculoskeletal models: A pilot study en
dc.type Journal Article en
dc.identifier.doi 10.1016/j.compbiomed.2017.05.007 en
pubs.begin-page 82 en
pubs.volume 86 en
dc.rights.holder Copyright: Elsevier en
dc.identifier.pmid 28511122 en
pubs.end-page 89 en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Article en
pubs.elements-id 626271 en
pubs.org-id Engineering en
pubs.org-id Mechanical Engineering en
dc.identifier.eissn 1879-0534 en
pubs.record-created-at-source-date 2017-05-18 en
pubs.online-publication-date 2017-05-10 en
pubs.dimensions-id 28511122 en


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