BCI training to move a virtual hand reduces phantom limb pain: A randomized crossover trial

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Objective: To determine whether training with a brain–computer interface (BCI) to control an image of a phantom hand, which moves based on cortical currents estimated from magnetoencephalographic signals, reduces phantom limb pain. Methods: Twelve patients with chronic phantom limb pain of the upper limb due to amputation or brachial plexus root avulsion participated in a randomized single-blinded crossover trial. Patients were trained to move the virtual hand image controlled by the BCI with a real decoder, which was constructed to classify intact hand movements from motor cortical currents, by moving their phantom hands for 3 days (“real training”). Pain was evaluated using a visual analogue scale (VAS) before and after training, and at follow-up for an additional 16 days. As a control, patients engaged in the training with the same hand image controlled by randomly changing values (“random training”). The 2 trainings were randomly assigned to the patients. This trial is registered at UMIN-CTR (UMIN000013608). Results: VAS at day 4 was significantly reduced from the baseline after real training (mean [SD], 45.3 [24.2]–30.9 [20.6], 1/100 mm; p = 0.009 < 0.025), but not after random training (p = 0.047 > 0.025). Compared to VAS at day 1, VAS at days 4 and 8 was significantly reduced by 32% and 36%, respectively, after real training and was significantly lower than VAS after random training (p < 0.01). Conclusion: Three-day training to move the hand images controlled by BCI significantly reduced pain for 1 week. Classification of evidence: This study provides Class III evidence that BCI reduces phantom limb pain.

収録刊行物

  • Neurology

    Neurology 95 (4), e417-e426, 2020-07-28

    Ovid Technologies (Wolters Kluwer Health)

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詳細情報 詳細情報について

  • CRID
    1050567175258265472
  • NII論文ID
    120006884163
  • ISSN
    00283878
    1526632X
  • HANDLE
    2433/254198
  • 本文言語コード
    en
  • 資料種別
    journal article
  • データソース種別
    • IRDB
    • CiNii Articles

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