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sEMG-Upper Limb Interaction Force Estimation Framework Based on Residual Network and Bidirectional Long Short-Term Memory Network

文献类型：期刊论文

作者Lu, Wei1,3; Gao, Lifu1,3; Cao, Huibin1,3; Li, Zebin1,2,3
刊名APPLIED SCIENCES-BASEL
出版日期2022-09-01
卷号12
关键词electromyography residual network bidirectional long short-term memory network interaction force estimation
DOI10.3390/app12178652
通讯作者Cao, Huibin(hbcao@iim.ac.cn) ; Li, Zebin(zebinli@163.com)
英文摘要It is of great significance to estimate the interaction force of upper limbs accurately for improving the control performance of human-computer interaction. However, due to the randomness of the input biological signals and the influence of environmental interference, the interaction force is difficult to estimate using the current methods. Therefore, based on the advantages of the Residual Network (ResNet) and Bidirectional Long Short-Term Memory Network (BiLSTM) model, this paper proposes an end-to-end regression model that integrates ResNet and BiLSTM with an attention mechanism. This model is more suitable for time series sEMG signals. Moreover, it improves the feature extraction ability of the signal and improves the accuracy of interaction force estimation. Experimental results show that this method can automatically extract effective features without professional knowledge. In addition, our method is superior to existing methods in estimation accuracy and generalization ability.
WOS关键词EMG ; MECHANOMYOGRAPHY ; MODEL
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA22040303] ; Key Research and Development Project of Anhui Province[2022a05020035] ; Major Science and Technology Project of Anhui Province[202103a05020022] ; National Natural Science Foundation of China[92067205] ; Natural Science Foundation of Anhui Province[1808085QF514] ; Key scientific research projects of Anhui Province higher education[KJ2020A0630]
WOS研究方向Chemistry ; Engineering ; Materials Science ; Physics
语种英语
WOS记录号WOS:000850964900001
出版者MDPI
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences ; Key Research and Development Project of Anhui Province ; Major Science and Technology Project of Anhui Province ; National Natural Science Foundation of China ; Natural Science Foundation of Anhui Province ; Key scientific research projects of Anhui Province higher education
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/128866]  
专题中国科学院合肥物质科学研究院
通讯作者Cao, Huibin; Li, Zebin
作者单位1.Chinese Acad Sci, Inst Intelligent Machines, Hefei Inst Phys Sci, Hefei 230031, Peoples R China
2.West Anhui Univ, Sch Elect & Photoelect Engn, Luan 237012, Peoples R China
3.Univ Sci & Technol China, Dept Sci Isl, Hefei 230026, Peoples R China
推荐引用方式
GB/T 7714		 Lu, Wei,Gao, Lifu,Cao, Huibin,et al. sEMG-Upper Limb Interaction Force Estimation Framework Based on Residual Network and Bidirectional Long Short-Term Memory Network[J]. APPLIED SCIENCES-BASEL,2022,12.
APA Lu, Wei,Gao, Lifu,Cao, Huibin,&Li, Zebin.(2022).sEMG-Upper Limb Interaction Force Estimation Framework Based on Residual Network and Bidirectional Long Short-Term Memory Network.APPLIED SCIENCES-BASEL,12.
MLA Lu, Wei,et al."sEMG-Upper Limb Interaction Force Estimation Framework Based on Residual Network and Bidirectional Long Short-Term Memory Network".APPLIED SCIENCES-BASEL 12(2022).

入库方式： OAI收割

来源：合肥物质科学研究院

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