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Invariant Spatial Parametrization of Human Thoracohumeral Kinematics: A Feasibility Study
KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.ORCID iD: 0000-0002-5970-2985
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0003-2078-8854
2016 (English)In: 2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016), IEEE, 2016, 4469-4476 p.Conference paper (Refereed)
Abstract [en]

In this paper, we present a novel kinematic framework using hybrid twists, that has the potential to improve the reliability of estimated human shoulder kinematics. This is important as the functional aspects of the human shoulder are evaluated using the information embedded in thoracohumeral kinematics. We successfully demonstrate in our results, that our approach is invariant of the body-fixed coordinate definition, is singularity free and has high repeatability; thus resulting in a flexible user-specific kinematic tracking not restricted to bony landmarks.

Place, publisher, year, edition, pages
IEEE, 2016. 4469-4476 p.
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-202810ISI: 000391921704074ISBN: 978-1-5090-3762-9 OAI: oai:DiVA.org:kth-202810DiVA: diva2:1079020
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), OCT 09-14, 2016, Daejeon, SOUTH KOREA
Note

QC 20170307

Available from: 2017-03-07 Created: 2017-03-07 Last updated: 2017-03-08Bibliographically approved

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http://www.iros2016.org/

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Rakesh, KrishnanSmith, Christian
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