CASIA OpenIR
A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation
Luo, Lincong1,2; Peng, Liang1; Wang, Chen1,2,3; Hou, Zeng-Guang1,2
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN2162-237X
2019-11-01
Volume30Issue:11Pages:3433-3443
Corresponding AuthorHou, Zeng-Guang(zengguang.hou@ia.ac.cn)
AbstractPrevious 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.
KeywordMedical 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
DOI10.1109/TNNLS.2019.2892157
WOS KeywordROBOTIC ASSISTANCE ; IMPEDANCE CONTROL ; STROKE ; MODEL
Indexed BySCI
Language英语
Funding ProjectNational 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] ; 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]
Funding OrganizationNational Natural Science Foundation of China ; Beijing Natural Science Foundation ; Strategic Priority Research Program of Chinese Academy of Science
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000494702100018
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/28919
Collection中国科学院自动化研究所
Corresponding AuthorHou, Zeng-Guang
Affiliation1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
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.
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