The rutgers arm II rehabilitation system-A feasibility study

Grigore C. Burdea, Daniel Cioi, Joseph Martin, Devin Fensterheim, Maeve Holenski

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

The Rutgers Arm II (RA II) is a new system that trains the shoulder/arm motor control, strengthening, arm speed of motion, endurance, and grasp strength in a single rehabilitation session. The system components are a tilted low-friction table, a forearm support with markers and wireless transmitter, a shoulder appendage to detect compensatory leaning, infrared vision tracking, a large display and a PC running custom virtual reality games. Three participants in the chronic stage post-stroke were trained on the RAII for four weeks (12 sessions) and had a follow-up evaluation after three months. The results of this study indicate that the participants were able to use the technology, and preliminary results are encouraging. One participant showed improvement in all timed Jebsen-Taylor test tasks, all participants had a larger shoulder range-ofmotion and pinch strength of the affected hand post-training. Computerized measure of supported arm reach area increased in two participants post-training and in all participants at follow-up. Participants reported an improved ability to perform activities of daily living with the affected arm. There was good compliance by the participants, each of whom attended all sessions. The participants accepted the training length, even with some sessions lasting 1 h (excluding rest periods). The participants' subjective evaluation rated the system an average 3.7 out of 5 (see also the accompanying taped video interview of one of the participants).

Original languageEnglish (US)
Article number5482032
Pages (from-to)505-514
Number of pages10
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume18
Issue number5
DOIs
StatePublished - Oct 2010

All Science Journal Classification (ASJC) codes

  • Internal Medicine
  • Neuroscience(all)
  • Biomedical Engineering

Keywords

  • Grasp strength
  • gravity
  • infrared tracking
  • stroke
  • upper extremity
  • virtual reality

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