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

文献类型：期刊论文

作者Luo, Lincong1,2; Peng, Liang2; Wang, Chen1,2,3; Hou, Zeng-Guang1,2
刊名IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
出版日期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
DOI10.1109/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.
WOS关键词ROBOTIC ASSISTANCE ; IMPEDANCE CONTROL ; STROKE ; MODEL
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研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000494702100018
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Strategic Priority Research Program of Chinese Academy of Science
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.

入库方式： OAI收割

来源：自动化研究所

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