Sequentially applied myoelectrically controlled FES in a task-oriented approach and robotic therapy for the recovery of upper limb in post-stroke patients: A randomized controlled pilot study

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Abstract

BACKGROUND: Functional recovery of the plegic upper limb in post-stroke patients may be enhanced by sequentially applying a myoelectrically controlled FES (MeCFES), which allows the patient to voluntarily control the muscle contraction during a functional movement, and robotic therapy which allows many repetitions of movements. OBJECTIVE: Evaluate the efficacy of MeCFES followed by robotic therapy compared to standard care arm rehabilitation for post-stroke patients. METHODS: Eighteen stroke subjects (onset ⩾ 3 months, age 60.1 ± 15.5) were recruited and randomized to receive an experimental combination of MeCFES during task-oriented reaching followed by robot therapy (MRG) or same intensity conventional rehabilitation care (CG) aimed at the recovery of the upper limb (20 sessions/45 minutes). Change was evaluated through Fugl-Meyer upper extremity (FMA-UE), Reaching Performance Scale and Box and Block Test. RESULTS: The experimental treatment resulted in higher improvement on the FMA-UE compared with CG (P= 0.04), with a 10-point increase following intervention. Effect sizes were moderate in favor of the MRG group on FMA-UE, FMA-UE proximal and RPS (0.37-0.56). CONCLUSIONS: Preliminary findings indicate that a combination of MeCFES and robotic treatment may be more effective than standard care for recovery of the plegic arm in persons > 3 months after stroke. The mix of motor learning techniques may be important for successful rehabilitation of arm function.

Original languageEnglish
Pages (from-to)419-429
Number of pages11
JournalTechnology and Health Care
Volume29
Issue number3
DOIs
Publication statusPublished - 2021

Keywords

  • arm function
  • combined approaches
  • myoelectrically controlled FES
  • robot rehabilitation
  • Stroke

ASJC Scopus subject areas

  • Biophysics
  • Bioengineering
  • Information Systems
  • Biomaterials
  • Biomedical Engineering
  • Health Informatics

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