ArmAssist Robotic System versus Matched Conventional Therapy for Poststroke Upper Limb Rehabilitation: A Randomized Clinical Trial.

Journal: BioMed research international
Published Date:

Abstract

The ArmAssist is a simple low-cost robotic system for upper limb motor training that combines known benefits of repetitive task-oriented training, greater intensity of practice, and less dependence on therapist assistance. The aim of this preliminary study was to compare the efficacy of ArmAssist (AA) robotic training against matched conventional arm training in subacute stroke subjects with moderate-to-severe upper limb impairment. Twenty-six subjects were enrolled within 3 months of stroke and randomly assigned to the AA group or Control group ( = 13 each). Both groups were trained 5 days per week for 3 weeks. The primary outcome measure was Fugl-Meyer Assessment-Upper Extremity (FMA-UE) motor score, and the secondary outcomes were Wolf Motor Function Test-Functional Ability Scale (WMFT-FAS) and Barthel index (BI). The AA group, in comparison to the Control group, showed significantly greater increases in FMA-UE score (18.0 ± 9.4 versus 7.5 ± 5.5, = 0.002) and WMFT-FAS score (14.1 ± 7.9 versus 6.7 ± 7.8, = 0.025) after 3 weeks of treatment, whereas the increase in BI was not significant (21.2 ± 24.8 versus 13.1 ± 10.7, = 0.292). There were no adverse events. We conclude that arm training using the AA robotic device is safe and able to reduce motor deficits more effectively than matched conventional arm training in subacute phase of stroke. The study has been registered at the ClinicalTrials.gov, ID: NCT02729649.

Authors

  • Tijana J Dimkić Tomić
    Clinic for Rehabilitation "Dr. Miroslav Zotović", Faculty of Medicine, University Belgrade, Sokobanjska 13, 11000 Belgrade, Serbia.
  • Andrej M Savić
    Tecnalia Serbia Ltd., Vladetina 13 and Signals and Systems Department, School of Electrical Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, 11200 Belgrade, Serbia.
  • Aleksandra S Vidaković
    Clinic for Rehabilitation "Dr. Miroslav Zotović", Faculty of Medicine, University Belgrade, Sokobanjska 13, 11000 Belgrade, Serbia.
  • Sindi Z Rodić
    Clinic for Rehabilitation "Dr. Miroslav Zotović", Faculty of Medicine, University Belgrade, Sokobanjska 13, 11000 Belgrade, Serbia.
  • Milica S Isaković
    Tecnalia Serbia Ltd., Vladetina 13 and Signals and Systems Department, School of Electrical Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, 11200 Belgrade, Serbia.
  • Cristina Rodríguez-de-Pablo
    Neurorehabilitation Area at the Health Division of TECNALIA, San Sebastian, Spain.
  • Thierry Keller
    TECNALIA Research & Innovation, Health Division, Mikeletegi Pasealekua 1-3, 20009 Donostia-San Sebastián, Spain . Electronic address: thierry.keller@tecnalia.com.
  • Ljubica M Konstantinović
    Clinic for Rehabilitation "Dr. Miroslav Zotović", Faculty of Medicine, University Belgrade, Sokobanjska 13, 11000 Belgrade, Serbia.