Arm motion analysis of stroke patients in activities of daily living tasks: A preliminary study

Kyung Kim, Dae Sung Park, Byung Woo Ko, Jeongsu Lee, Seung Nam Yang, Jongbae Kim, Won Kyung Song

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

11 Citations (Scopus)

Abstract

Analyzing activities of daily living (ADL) for the development of practical upper limb rehabilitation robots is challenging in stroke patients. Basic ADL tasks using an upper limb are defined based on clinical assessment tools. The motions of 8 healthy participants and 8 stroke patients were recorded during defined ADL tasks, and then analyzed with respect to completion time, linearity of motion, and range of motion of the joints. Completion time and motion trajectories were significantly different between stroke subjects and healthy participants. For tasks involving the transfer of an object from a table to the user's mouth, wrist radial-ulnar deviation motions should be taken into account while designing robots for gross movements via elbow and shoulder joints. Our findings can be extended to the design of trajectories of rehabilitation robots as well as of simplified robots.

Original languageEnglish
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages1287-1291
Number of pages5
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: 2011 Aug 302011 Sep 3

Publication series

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

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period11/8/3011/9/3

ASJC Scopus subject areas

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

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