A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation

doi:10.1109/TNNLS.2019.2892157

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进机器人控制团队

	A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation
	Luo, Lincong 1,2; Peng, Liang 2; Wang, Chen 1,2,3; Hou, Zeng-Guang 1,2
刊名	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2019-11-01
卷号	30 期号:11 页码:3433-3443
关键词	Medical treatment Training Task analysis Robot sensing systems Impedance Trajectory Assist as needed (AAN) challenge level Gaussian radial basis function (RBF) network motor capability rehabilitation robot upper limb
ISSN号	2162-237X
DOI	10.1109/TNNLS.2019.2892157
通讯作者	Hou, Zeng-Guang(zengguang.hou@ia.ac.cn)
英文摘要	Previous studies on robotic rehabilitation have shown that subjects' active participation and effort involved in rehabilitation training can promote the performance of therapies. In order to improve the voluntary effort of participants during the rehabilitation training, assist-as-needed (AAN) control strategies regulating the robotic assistance according to subjects' performance and conditions have been developed. Unfortunately, the heterogeneity of patients' motor function capability in task space is not taken into account during the implementation of these controllers. In this paper, a new scheme called greedy AAN (GAAN) controller is designed for the upper limb rehabilitation training of neurologically impaired subjects. The proposed GAAN control paradigm includes a baseline controller and a Gaussian RBF network that is utilized to model the functional capability of subjects and to provide corresponding a task challenge for them. In order to avoid subjects' slacking and encourage their active engagement, the weight vectors of RBF networks evaluating subjects' impairment level are updated based on a greedy strategy that makes the networks progressively learn the maximum forces over time provided by subjects. Simultaneously, a challenge level modification algorithm is employed to adjust the task challenge according to the task performance of subjects. Experiments on 12 subjects with neurological impairment are conducted to validate the performance and feasibility of the GAAN controller. The results show that the proposed GAAN controller has significant potential to promote the subjects' voluntary engagement during training exercises.
资助项目	National Natural Science Foundation of China[61720106012] ; National Natural Science Foundation of China[61533016] ; National Natural Science Foundation of China[61603386] ; National Natural Science Foundation of China[U1613228] ; Beijing Natural Science Foundation[3171001] ; Beijing Natural Science Foundation[L172050] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32040000]
WOS关键词	ROBOTIC ASSISTANCE ; IMPEDANCE CONTROL ; STROKE ; MODEL
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000494702100018
资助机构	National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Strategic Priority Research Program of Chinese Academy of Science
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/28918]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者	Hou, Zeng-Guang
作者单位	1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China 3.CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Luo, Lincong,Peng, Liang,Wang, Chen,et al. A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2019,30(11):3433-3443.
APA	Luo, Lincong,Peng, Liang,Wang, Chen,&Hou, Zeng-Guang.(2019).A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,30(11),3433-3443.
MLA	Luo, Lincong,et al."A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 30.11(2019):3433-3443.