机器人外科学杂志（中英文）2021，Vol.2Issue(4)：295-305,11.DOI:10.12180/j.issn.2096-7721.2021.04.008
Elman神经网络在表面肌电连续估计肘关节角度中的应用
Application of Elman neural network in continuous estimation of elbow joint angle with sEMG
摘要
Abstract
Objective: To estimate the elbow joint angle and improve the rapidity and precision of the model. Methods: The elman neural network (ENN) based on surface electromyogram (sEMG) was established and investigated. The sEMG signals were collected by the electrodes placed on the skin surfaces of biceps muscle (BM) and triceps muscle (TM), and the actual elbow joint angle was recorded by an inertial measurement unit (IMU). Results: Theoretical analysis indicates that the ENN is feasible to be employed for estimating the elbow joint angle. Experimental results and the parameter discussion based on the model order and the number of hidden layer neurons further indicate that the minimum RMS error of ENN is 18.1899 degree. Conclusion: The RMS error is controllable when the ENN is used to estimate the elbow joint angle under the optimal parameter. Theoretical analysis and experimental results shows that the ENN is effective in estimation of joint angles.关键词
表面肌电信号/Elman神经网络/均方根/意图识别/康复Key words
sEMG/Elman neural network/RMS/Intention recognition/Rehabilitation分类
医药卫生引用本文复制引用
刘永柏,王刚,柴媛媛,刘克平,金龙,孙中波..Elman神经网络在表面肌电连续估计肘关节角度中的应用[J].机器人外科学杂志（中英文）,2021,2(4):295-305,11.基金项目
国家自然科学基金项目(6187330) （6187330）
中国博士后科学基金项目(2018M641784,2019T120240) （2018M641784,2019T120240）
吉林省科技发展计划项目(20200404208YY,20200201291JC)National Natural Science Foundation of China (61873304) （20200404208YY,20200201291JC）
China Postdoctoral Science Foundation Project (2018M641784, 2019T120240) （2018M641784, 2019T120240）
Key Science and Technology Projects of Jilin Province, China (20200404208YY, 20200201291JC) （20200404208YY, 20200201291JC）
