Real-time 3D control of a robot arm based on a brain-machine interface using intracranial EEG

DOI
  • Kuratomi Takeru
    Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Osaka, Japan
  • Palmer Jason
    Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Osaka, Japan
  • Chen Peng
    Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering, The University of Electro-Communications
  • Jiang Yinlai
    Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering, The University of Electro-Communications
  • Yokoi Hiroshi
    Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering, The University of Electro-Communications
  • Hirata Masayuki
    Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Osaka, Japan

Bibliographic Information

Other Title
  • 頭蓋内脳波を用いたブレインマシンインターフェースによるロボットアームの３次元リアルタイム制御

Description

<p>Objective: We aimed to estimate the velocity vector of the wrist based on the human intracranial electroencephalography (iEEG) and to control a robot arm three-dimensionally. </p><p>Methods: An epilepsy patient with implanted intracranial electrodes participated in this study. IEEGs were recorded while the patient imitated simulated movement of a robot arm. Independent component analysis (ICA) and partial least squares regression (PLS) were used to extract components specifically distributed over the sensorimotor areas. These components were used to estimate the wrist velocity vector using support vector regression (SVR). The robot arm was three-dimensionally controlled based on the estimated velocity using ROS where inverse kinematics were implemented.</p><p>Results: We developed the system for real-time three-dimensional control of a robot arm by estimating the wrist velocity based on iEEG using ICA, PLS and SVR.</p><p>Conclusion: Three-dimensional velocity control based on iEEG, ICA, PLS and SVR is feasible for real-time control of a robot arm.</p>

Journal

Details 詳細情報について

  • CRID
    1390289765041405440
  • NII Article ID
    130008105259
  • DOI
    10.11239/jsmbe.annual59.329
  • ISSN
    18814379
    1347443X
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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