A Control Framework for Adaptation of Training Task and Robotic Assistance for Promoting Motor Learning With an Upper Limb Rehabilitation Robot

doi:10.1109/TSMC.2022.3163916

	A Control Framework for Adaptation of Training Task and Robotic Assistance for Promoting Motor Learning With an Upper Limb Rehabilitation Robot
	Wang, Chen1 ; Peng, Liang1 ; Hou, Zeng-Guang1,2,3
发表期刊	IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
ISSN	2168-2216
	2022-04-15
页码	11
通讯作者	Hou, Zeng-Guang(zengguang.hou@ia.ac.cn)
摘要	Robot-assisted rehabilitation has been a promising solution to improve motor learning of neurologically impaired patients. State-of-the-art control strategies are typically limited to the ignorance of heterogeneous motor capabilities of poststroke patients and therefore intervene suboptimally. In this article, we propose a control framework for robot-assisted motor learning, emphasizing the detection of human intention, generation of reference trajectories, and modification of robotic assistance. A real-time trajectory generation algorithm is presented to extract the high-level features in active arm movements using an adaptive frequency oscillator (AFO) and then integrate the movement rhythm with the minimum-jerk principle to generate an optimal reference trajectory, which synchronizes with the motion intention in the patient as well as the motion pattern in healthy humans. In addition, a subject-adaptive assistance modification algorithm is presented to model the patient's residual motor capabilities employing spatially dependent radial basis function (RBF) networks and then combining the RBF-based feedforward controller with the impedance feedback controller to provide only necessary assistance while simultaneously regulating the maximum-tolerated error during trajectory tracking tasks. We conduct simulation and experimental studies based on an upper limb rehabilitation robot to evaluate the overall performance of the motor-learning framework. A series of results showed that the difficulty level of reference trajectories was modulated to meet the requirements of subjects' intended motion, furthermore, the robotic assistance was compliantly optimized in response to the changing performance of subjects' motor abilities, highlighting the potential of adopting our framework into clinical application to promote patient-led motor learning.
关键词	Robots Trajectory Task analysis Training Oscillators Rehabilitation robotics Real-time systems Assist as needed (AAN) motor learning nonlinear adaptive control rehabilitation robotics
DOI	10.1109/TSMC.2022.3163916
关键词[WOS]	EXOSKELETON
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFB1307000] ; National Natural Science Foundation of China[U1913601] ; National Natural Science Foundation of China[61720106012] ; Major Scientific and Technological Innovation Projects in Shandong Province[2019JZZY011111] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32040000]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Major Scientific and Technological Innovation Projects in Shandong Province ; Strategic Priority Research Program of Chinese Academy of Science
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Cybernetics
WOS记录号	WOS:000785818900001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	多模态智能
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/48385
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Hou, Zeng-Guang
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wang, Chen,Peng, Liang,Hou, Zeng-Guang. A Control Framework for Adaptation of Training Task and Robotic Assistance for Promoting Motor Learning With an Upper Limb Rehabilitation Robot[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2022:11.
APA	Wang, Chen,Peng, Liang,&Hou, Zeng-Guang.(2022).A Control Framework for Adaptation of Training Task and Robotic Assistance for Promoting Motor Learning With an Upper Limb Rehabilitation Robot.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,11.
MLA	Wang, Chen,et al."A Control Framework for Adaptation of Training Task and Robotic Assistance for Promoting Motor Learning With an Upper Limb Rehabilitation Robot".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2022):11.