Individuals with Chronic Hemiparetic Stroke Correctly Match Forearm Position Within a Single Arm: Preliminary Findings

  • Erik J. EuvingEmail author
  • Netta Gurari
  • Justin M. Drogos
  • Stuart Traxel
  • Arno H. A. Stienen
  • Julius P. A. Dewald
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9774)


According to between arms position matching assessments, more than 50 % of individuals with stroke may have moderate to severe proprioceptive deficits. This study is the first of a series of studies designed to investigate the reason for observed between arms position matching deficits. In this work, we quantified the ability of five participants with chronic hemiparetic stroke (participants with stroke) and five age-matched participants without neurological impairments (controls) to match forearm positions within a single arm. According to the revised Nottingham Sensory Assessment, the participants with stroke all had impaired forearm position sense and unimpaired forearm movement direction sense, while the controls had unimpaired forearm position and movement direction sense. A custom robotic device was used to quantify each participant’s task performance during active movements when performing a single arm memory matching task. Participants were asked to match the location of the forearm with a remembered target location. Results show that the participants with stroke identified the target location just as well as the controls. Based on our findings, we suggest that our participants with chronic hemiparetic stroke, who have deficits in matching forearm positions across both arms, may not have impaired forearm position sense within a single arm, and we suggest that the position matching deficits may arise for non-sensory related reasons. Future work will continue to use such behavioral studies to investigate possible central neural mechanisms that may be contributing to the observed between arms position matching deficits.


Target Location Elbow Joint Constant Error Robotic Device Target Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Arvid Keemink for his assistance with the software, Paul Krueger and Di Zhang for their assistance with the hardware, Carolina Carmona for her assistance with the data collection, the participants who partook in the experiment and the anonymous reviewers for their feedback.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Erik J. Euving
    • 1
    Email author
  • Netta Gurari
    • 2
  • Justin M. Drogos
    • 2
  • Stuart Traxel
    • 2
  • Arno H. A. Stienen
    • 1
    • 2
  • Julius P. A. Dewald
    • 1
    • 2
    • 3
    • 4
  1. 1.Faculty of Engineering Technology, Department of Biomechanical EngineeringUniversity of TwenteEnschedeThe Netherlands
  2. 2.Department of Physical Therapy and Human Movement SciencesNorthwestern UniversityChicagoUSA
  3. 3.Department of Biomedical EngineeringNorthwestern UniversityChicagoUSA
  4. 4.Department of Physical Medicine and RehabilitationNorthwestern UniversityChicagoUSA

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