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Segmenting Humeral Submovements using Invariant Geometric Signatures
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics. Robotics, Perception and Learning, School of Computer Science and Communication, KTH - Royal Institute of Technology, Stockholm, Sweden..ORCID iD: 0000-0002-5970-2985
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.ORCID iD: 0000-0001-5429-7223
Robotics, Perception and Learning, School of Computer Science and Communication, KTH - Royal Institute of Technology, Stockholm, Sweden..ORCID iD: 0000-0003-2078-8854
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Discrete submovements are the building blocks of any complex movement. When robots collaborate with humans, extraction of such submovements can bevery helpful in applications such as robot-assisted rehabilitation. Our work aims to segment these submovements based on the invariant geometric information embedded in segment kinematics. Moreover, this segmentation is achieved without any explicit kinematic representation.Our work demonstrates the usefulness of this invariant framework in segmenting a variety of humeral movements, which are performed at different speeds across different subjects. Our results indicate that this invariant framework has high computational reliability despite the inherent variability in human motion.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Kinematics, Human Movement Understanding, Human-centric Robotics
National Category
Robotics
Identifiers
URN: urn:nbn:se:hig:diva-25214OAI: oai:DiVA.org:hig-25214DiVA: diva2:1140530
Conference
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017), 24–28 September 2017, Vancouver, Canada
Funder
VINNOVA, AAL 2013-6-042
Note

Forthcoming

Available from: 2017-09-12 Created: 2017-09-12 Last updated: 2017-09-12Bibliographically approved

Open Access in DiVA

fulltext(1163 kB)11 downloads
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf