Robotic neurorehabilitation system design for stroke patients

被引：12

作者：

Xu, Baoguo ^{[1
]}

Song, Aiguo ^{[1
]}

Zhao, Guopu ^{[2
]}

Xu, Guozheng ^{[3
]}

Pan, Lizheng ^{[4
]}

Yang, Renhuan ^{[5
]}

Li, Huijun ^{[1
]}

Cui, Jianwei ^{[1
]}

Zeng, Hong ^{[1
]}

机构：

[1] Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China

[2] Jiangsu Siming Engn Machinery Co Ltd, Yangzhou, Jiangsu, Peoples R China

[3] Nanjing Univ Posts & Telecommun, Coll Automat, Nanjing, Jiangsu, Peoples R China

[4] Changzhou Univ, Sch Mech Engn, Changzhou, Peoples R China

[5] Jinan Univ, Coll Informat Sci & Technol, Guangzhou, Guangdong, Peoples R China

来源：

ADVANCES IN MECHANICAL ENGINEERING | 2015年 / 7卷 / 03期

基金：

国家高技术研究发展计划(863计划);

关键词：

Stroke; robotic therapy; fuzzy control; gait rehabilitation; BRAIN-COMPUTER INTERFACE; DENTAL ARCH GENERATOR; REHABILITATION; THERAPY;

D O I：

10.1177/1687814015573768

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

In this article, a neurorehabilitation system combining robot-aided rehabilitation with motor imagery-based brain-computer interface is presented. Feature extraction and classification algorithm for the motor imagery electroencephalography is implemented under our brain-computer interface research platform. The main hardware platform for functional recovery therapy is the Barrett Whole-Arm Manipulator. The mental imagination of upper limb movements is translated to trigger the Barrett Whole-Arm Manipulator Arm to stretch the affected upper limb to move along the predefined trajectory. A fuzzy proportional-derivative position controller is proposed to control the Whole-Arm Manipulator Arm to perform passive rehabilitation training effectively. A preliminary experiment aimed at testing the proposed system and gaining insight into the potential of motor imagery electroencephalography-triggered robotic therapy is reported.

引用

页码：1 / 12

页数：12

共 27 条

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