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

被引：0

作者：

Kuratomi T. ^{[1
]}

Palmer J. ^{[1
]}

Chen P. ^{[2
]}

Jiang Y. ^{[2
]}

Yokoi H. ^{[2
]}

Hirata M. ^{[1
]}

机构：

[1] Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University

[2] Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering, The University of Electro-Communications

来源：

Transactions of Japanese Society for Medical and Biological Engineering | 2021年 / Annual 59卷 / Proc期

关键词：

Bio-robotics; Brain-machine Interface; Intracranial Electroencephalogram; Neural Decoding;

D O I：

10.11239/jsmbe.Annual59.638

中图分类号：

学科分类号：

摘要：

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. 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. 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. Conclusion: Three-dimensional velocity control based on iEEG, ICA, PLS and SVR is feasible for real-time control of a robot arm. © 2021, Japan Soc. of Med. Electronics and Biol. Engineering. All rights reserved.

引用

页码：638 / 640

页数：2

共 5 条

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