Development and evaluation of haptics-based rehabilitation system

Shrey Pareek, Pramod Chembrammel, Thenkurussi Kesavadas

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


In this paper, we discuss the development and testing of a haptics-based stroke rehabilitation system. The system involves a 6-degrees of freedom haptic device and a virtual reality game designed to induce implicit learning in users. We present the preliminary usability/feasibility study of our system as a rehabilitation tool with 15 healthy subjects while using their non-dominant hand. The three-session study demonstrates improvements in all quantitative performance metrics of the learning tasks and the self-perceived workload levels of the subjects. We also studied the differences in performance arising due to three different assistance modes-no assistance, assist-as-needed, and continuous assistance. Comparing the differences in improvements of the performance metrics among the subject groups suggests that fewer sessions of assisted therapy may have the same effects as more sessions of unassisted therapy. We also observed that within the two assisted groups, the assist-as-needed strategy led to greater improvements than the continuously assisted group; which might be due to the lower mental/physical demand associated with the continuously assisted paradigm.

Original languageEnglish (US)
Title of host publication2018 International Symposium on Medical Robotics, ISMR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538625125
StatePublished - Apr 6 2018
Event2018 International Symposium on Medical Robotics, ISMR 2018 - Atlanta, United States
Duration: Mar 1 2018Mar 3 2018

Publication series

Name2018 International Symposium on Medical Robotics, ISMR 2018


Other2018 International Symposium on Medical Robotics, ISMR 2018
Country/TerritoryUnited States


  • assistive systems
  • robotic rehabilitation
  • stroke
  • tele-rehabilitation

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Artificial Intelligence


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