Calculating reachable workspace volume for use in quantitative medicine

Robert Peter Matthew, Gregorij Kurillo, Jay J. Han, Ruzena Bajcsy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Quantitative measures of the space an individual can reach is essential for tracking the progression of a disease and the effects of therapeutic intervention. The reachable workspace can be used to track an individuals’ ability to perform activities of daily living, such as feeding and grooming. There are few methods for quantifying upper limb performance, none of which are able to generate a reachable workspace volume from motion capture data. We introduce a method to estimate the reachable workspace volume for an individual by capturing their observed joint limits using a low cost depth camera. This method is then tested on seven individuals with varying upper limb performance. Based on these initial trials, we found that the reachable workspace volume decreased as muscular impairment increased. This shows the potential for this method to be used as a quantitative clinical assessment tool.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages570-583
Number of pages14
Volume8927
ISBN (Print)9783319161983
DOIs
StatePublished - 2015
Event13th European Conference on Computer Vision, ECCV 2014 - Zurich, Switzerland
Duration: Sep 6 2014Sep 12 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8927
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other13th European Conference on Computer Vision, ECCV 2014
CountrySwitzerland
CityZurich
Period9/6/149/12/14

Fingerprint

Workspace
Medicine
Data acquisition
Cameras
Costs
Motion Capture
Progression
Camera
Estimate

Keywords

  • Assessment
  • Diagnosis
  • Functional workspace
  • Goniometry
  • Kinect
  • Muscular dystrophy
  • Rehabilitation
  • Skeletal Modelling

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Matthew, R. P., Kurillo, G., Han, J. J., & Bajcsy, R. (2015). Calculating reachable workspace volume for use in quantitative medicine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8927, pp. 570-583). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8927). Springer Verlag. https://doi.org/10.1007/978-3-319-16199-0_40

Calculating reachable workspace volume for use in quantitative medicine. / Matthew, Robert Peter; Kurillo, Gregorij; Han, Jay J.; Bajcsy, Ruzena.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8927 Springer Verlag, 2015. p. 570-583 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8927).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Matthew, RP, Kurillo, G, Han, JJ & Bajcsy, R 2015, Calculating reachable workspace volume for use in quantitative medicine. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8927, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8927, Springer Verlag, pp. 570-583, 13th European Conference on Computer Vision, ECCV 2014, Zurich, Switzerland, 9/6/14. https://doi.org/10.1007/978-3-319-16199-0_40
Matthew RP, Kurillo G, Han JJ, Bajcsy R. Calculating reachable workspace volume for use in quantitative medicine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8927. Springer Verlag. 2015. p. 570-583. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-16199-0_40
Matthew, Robert Peter ; Kurillo, Gregorij ; Han, Jay J. ; Bajcsy, Ruzena. / Calculating reachable workspace volume for use in quantitative medicine. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8927 Springer Verlag, 2015. pp. 570-583 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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