A novel method for quantifying arm motion similarity

Zhi Li, Kris Hauser, Jay Ryan Roldan, Dejan Milutinovic, Jacob Rosen

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

Abstract

This paper proposes a novel task-independent method for quantifying arm motion similarity that can be applied to any kinematic/dynamic variable of interest. Given two arm motions for the same task, not necessarily with the same completion time, it plots the time-normalized curves against one another and generates four real-valued features. To validate these features we apply them to quantify the relationship between healthy and paretic arm motions of chronic stroke patients. Studying both unimanual and bimanual arm motions of eight chronic stroke patients, we find that inter-arm coupling that tends to synchronize the motions of both arms in bimanual motions, has a stronger effect at task-relevant joints than at task-irrelevant joints. It also revealed that the paretic arm suppresses the shoulder flexion of the non-paretic arm, while the latter encourages the shoulder rotation of the former.

Original languageEnglish (US)
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5716-5719
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - Nov 4 2015
Externally publishedYes
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/TerritoryItaly
CityMilan
Period8/25/158/29/15

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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