Knowledge Commons of Institute of Automation,CAS
Prediction of Human Voluntary Torques Based on Collaborative Neuromusculoskeletal Modeling and Adaptive Learning | |
Wang, Weiqun1,2; Shi, Weiguo1,2; Hou, Zeng-Guang1,2,3; Chen, Badong4; Liang, Xu1,2; Ren, Shixin1,2; Wang, Jiaxing1,2; Peng, Liang1,2 | |
发表期刊 | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS |
ISSN | 0278-0046 |
2021-06-01 | |
卷号 | 68期号:6页码:5217-5226 |
摘要 | Surface Electromyography (sEMG) based human-robot interaction has been widely studied, where prediction of human voluntary torques is one of the key issues that have not been well addressed. In this article, a torque prediction method based on collaborative neuromusculoskeletal modeling and adaptive learning, is proposed to overcome the limitation of existing methods. First, an sEMG-torque model is designed in comprehensive consideration of the previous research results, the requirement for subject-specific adjustment and the coupling between the muscle or muscle-tendon length and the adjacent joint angles, where the latter two factors have rarely been considered in the literature. Then, by combining the advantages of the stochastic particle swarm optimization and conjugate gradient algorithms, a collaborative optimization method is designed to calibrate simultaneously the undetermined parameters. Moreover, an adaptive learning method based on Gaussian process regression is proposed to learn and predict the estimation errors in real time, by which it is supposed that the torque prediction accuracy can be improved efficiently. Finally, experiments were carried out to validate the performance of the proposed method. |
关键词 | Muscles Adaptation models Adaptive learning Force Calibration Hip Electromyography Adaptive learning human– robot interaction neuromusculoskeletal modeling parameter calibration surface electromyography (sEMG) processing |
DOI | 10.1109/TIE.2020.2991999 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[91648208] ; National Natural Science Foundation of China[91848110] ; National Natural Science Foundation of China[U1913601] ; National Key R&D Program of China[2017YFB1302303] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32000000] |
项目资助者 | National Natural Science Foundation of China ; National Key R&D Program of China ; Strategic Priority Research Program of Chinese Academy of Science |
WOS研究方向 | Automation & Control Systems ; Engineering ; Instruments & Instrumentation |
WOS类目 | Automation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation |
WOS记录号 | WOS:000621470900060 |
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 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/43318 |
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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China 4.Jiaotong Univ, Inst Artificial Intelligence & Robot, Xian 710049, 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, Weiqun,Shi, Weiguo,Hou, Zeng-Guang,et al. Prediction of Human Voluntary Torques Based on Collaborative Neuromusculoskeletal Modeling and Adaptive Learning[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,2021,68(6):5217-5226. |
APA | Wang, Weiqun.,Shi, Weiguo.,Hou, Zeng-Guang.,Chen, Badong.,Liang, Xu.,...&Peng, Liang.(2021).Prediction of Human Voluntary Torques Based on Collaborative Neuromusculoskeletal Modeling and Adaptive Learning.IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS,68(6),5217-5226. |
MLA | Wang, Weiqun,et al."Prediction of Human Voluntary Torques Based on Collaborative Neuromusculoskeletal Modeling and Adaptive Learning".IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 68.6(2021):5217-5226. |
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