Wrist Angle Estimation With a Musculoskeletal Model Driven by Electrical Impedance Tomography Signals
文献类型：期刊论文
| 作者 | Zheng, Enhao4 ; Wan, Jiacheng1,4; Yang, Lin2,4; Wang, Qining3; Qiao, Hong4
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| 刊名 | IEEE ROBOTICS AND AUTOMATION LETTERS
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| 出版日期 | 2021-04-01 |
| 卷号 | 6期号:2页码:2186-2193 |
| 关键词 | Electrical impedance tomography human-machine interface musculoskeletal model wrist angle estimation |
| ISSN号 | 2377-3766 |
| DOI | 10.1109/LRA.2021.3060400 |
| 通讯作者 | Zheng, Enhao(enhao.zheng@ia.ac.cn) |
| 英文摘要 | Wrist kinematics estimation with muscle signals is a key issue in the field of wearable robots. In this study, we proposed a musculaskeletal-based-method driven by the Electrical Impedance Tomography (EIT) signals for continuously estimating wrist flexion/extension angles. The EIT-based interface can construct the conductivity distribution of the anatomical cross-sectional plane with a soft elastic sensing front-end, which is designed by our group. The estimation method took advantage of the flexor/extensor muscles' spatial information detected by the EIT-based interface to map the signals to the wrist angles. The whole model was designed with a musculoskeletal kinematic model, a muscular geometry model, and a mapping function between the EIT signals and the muscle morphological parameters. We validated the proposed method with intra-subject, inter-subject, and inter-posture cross-validations on 14 subjects in total. The results were compared with two data-driven algorithms (Lasso and kernel-based SVM). The muscle-model-based method was more robust to training data sizes than the other two methods. It achieved an average R-2 of 0.97 with 1:10 intra-subject CV and 0.91 with 2:12 inter-subject CV. The model also quickly overcame the effects of posture changes with a short-time feature update. The results of our study are comparable, if not better, to that of state-of-the-art. Future endeavors are worth being paid in this direction to get more promising outcomes. |
| 资助项目 | National Key Research and Development Program of China[2017YFB1300200] ; National Key Research and Development Program of China[2017YFB1300203] ; National Natural Science Foundation of China[61703400] ; National Natural Science Foundation of China[91648207] ; National Natural Science Foundation of China[51922015] |
| WOS研究方向 | Robotics |
| 语种 | 英语 |
| WOS记录号 | WOS:000629731200012 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/44145]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 通讯作者 | Zheng, Enhao |
| 作者单位 | 1.China Univ Geosci Beijing, Sch Informat Engn, Beijing 100083, Peoples R China 2.Beihang Univ, Sch Gen Engn, Beijing 100191, Peoples R China 3.Peking Univ, Coll Engn, Robot Res Grp, Beijing 100871, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zheng, Enhao,Wan, Jiacheng,Yang, Lin,et al. Wrist Angle Estimation With a Musculoskeletal Model Driven by Electrical Impedance Tomography Signals[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2021,6(2):2186-2193. |
| APA | Zheng, Enhao,Wan, Jiacheng,Yang, Lin,Wang, Qining,&Qiao, Hong.(2021).Wrist Angle Estimation With a Musculoskeletal Model Driven by Electrical Impedance Tomography Signals.IEEE ROBOTICS AND AUTOMATION LETTERS,6(2),2186-2193. |
| MLA | Zheng, Enhao,et al."Wrist Angle Estimation With a Musculoskeletal Model Driven by Electrical Impedance Tomography Signals".IEEE ROBOTICS AND AUTOMATION LETTERS 6.2(2021):2186-2193. |
入库方式： OAI收割
来源：自动化研究所
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