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Feasibility of task-specific brain-machine interface training for upper-extremity paralysis in patients with chronic hemiparetic stroke. | LitMetric

AI Article Synopsis

  • A new brain-machine interface system was created for upper-extremity rehabilitation to help patients with severe hemiparesis from strokes, focusing on real-world feasibility.
  • In a study with 26 patients, participants completed 10 days of training using the system alongside standard occupational therapy, which involved tasks like picking up and releasing pegs.
  • Results indicated significant improvement in motor function and satisfaction among therapists using the system, confirming its effectiveness and practicality in clinical settings.

Article Abstract

Objective: Brain-machine interface training was developed for upper-extremity rehabilitation for patients with severe hemiparesis. Its clinical application, however, has been limited because of its lack of feasibility in real-world rehabilitation settings. We developed a new compact task-specific brain-machine interface system that enables task-specific training, including reach-and-grasp tasks, and studied its clinical feasibility and effectiveness for upper-extremity motor paralysis in patients with stroke.

Design: Prospective beforeâ€"after study.

Subjects: Twenty-six patients with severe chronic hemiparetic stroke.

Methods: Participants were trained with the brain-machine interface system to pick up and release pegs during 40-min sessions and 40 min of standard occupational therapy per day for 10 days. Fugl-Meyer upper-extremity motor (FMA) and Motor Activity Log-14 amount of use (MAL-AOU) scores were assessed before and after the intervention. To test its feasibility, 4 occupational therapists who operated the system for the first time assessed it with the Quebec User Evaluation of Satisfaction with assistive Technology (QUEST) 2.0.

Results: FMA and MAL-AOU scores improved significantly after brain-machine interface training, with the effect sizes being medium and large, respectively (p<0.01, d=0.55; p<0.01, d=0.88). QUEST effectiveness and safety scores showed feasibility and satisfaction in the clinical setting.

Conclusion: Our newly developed compact brain-machine interface system is feasible for use in real-world clinical settings.

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Source
http://dx.doi.org/10.2340/16501977-2275DOI Listing

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