Real-time control of a neuroprosthetic hand by magnetoencephalographic signals from paralysed patients

• 神谷, 之康

• Yanagisawa, Takufumi

• Saitoh, Youichi

• Hosomi, Koichi

• Kishima, Haruhiko

• Shimizu, Takeshi

• Sugata, Hisato

• Yokoi, Hiroshi

• Hirata, Masayuki

• Kamitani, Yukiyasu

• Yoshimine, Toshiki

抄録

Neuroprosthetic arms might potentially restore motor functions for severely paralysed patients. Invasive measurements of cortical currents using electrocorticography have been widely used for neuroprosthetic control. Moreover, magnetoencephalography (MEG) exhibits characteristic brain signals similar to those of invasively measured signals. However, it remains unclear whether non-invasively measured signals convey enough motor information to control a neuroprosthetic hand, especially for severely paralysed patients whose sensorimotor cortex might be reorganized. We tested an MEG-based neuroprosthetic system to evaluate the accuracy of using cortical currents in the sensorimotor cortex of severely paralysed patients to control a prosthetic hand. The patients attempted to grasp with or open their paralysed hand while the slow components of MEG signals (slow movement fields; SMFs) were recorded. Even without actual movements, the SMFs of all patients indicated characteristic spatiotemporal patterns similar to actual movements, and the SMFs were successfully used to control a neuroprosthetic hand in a closed-loop condition. These results demonstrate that the slow components of MEG signals carry sufficient information to classify movement types. Successful control by paralysed patients suggests the feasibility of using an MEG-based neuroprosthetic hand to predict a patient's ability to control an invasive neuroprosthesis via the same signal sources as the non-invasive method.

[Corrigendum (19 October 2016)] Scientific Reports 6: Article number:34970 ; published online: 19 October 2016: doi:10.1038/srep34970

収録刊行物

• Scientific Reports

  Scientific Reports 6 2016-02-24

  Nature Publishing Group

詳細情報

• CRID: 1050282810812381056
• NII論文ID: 120005818285
• ISSN: 20452322
• HANDLE: 2433/216024
• 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