機能的近赤外分光法を用いたブレイン・コンピュータ・インタフェースに対する頭皮血流除去の効果

DOI Web Site Web Site 参考文献20件

書誌事項

タイトル別名
  • Effectiveness of Scalp-hemodynamics Reduction to Brain-computer Interfaces by Functional Near-infrared Spectroscopy
  • キノウテキ キンセキガイ ブンコウホウ オ モチイタ ブレイン ・ コンピュータ ・ インタフェース ニ タイスル アタマ ヒ ケツリュウ ジョキョ ノ コウカ

この論文をさがす

抄録

<p>Brain-computer interfaces (BCIs) are systems that control external devices by decoding information from brain activity signals. Functional near-infrared spectroscopy (fNIRS) has been used in many BCIs because of its simplicity of use and portability. However, hemodynamic changes in the scalp layer (scalp-hemodynamics) often contaminate fNIRS signals, and cause degradation of the detection accuracy of functional brain activities. Although several reduction methods have been proposed, no study has investigated their effects on fNIRS-BCI accuracy. In this study, we investigated the effects of applying scalp-hemodynamics reduction to the classification of for four tasks: ball grasping with left-, right-, or both-hands, or resting without movements. We applied a method that combined short source-detector distance channels with a general linear model. Results showed that the binary-class classification accuracy of left- or right-hand and the multi-class classification accuracy of 3-class grasping were significantly improved, suggesting that the scalp-hemodynamics reduction may provide more accurate fNIRS-BCIs.</p>

収録刊行物

参考文献 (20)*注記

もっと見る

関連プロジェクト

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ