sEMG-based multi-joints motion estimation of lower limb utilizing deep convolutional neural network-Reference-Cited by-同舟云学术

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sEMG-based multi-joints motion estimation of lower limb utilizing deep convolutional neural network

Published:2022-07-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)
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Author:

Wang Gang¹,Liu Yongbai¹,Shen Yao²,Chen Yan³,Liu Keping¹,Sun Zhongbo²

Affiliation:

1. Changchun University of Technology,Department of Mechanical Engineering,Changchun,China,130012

2. Changchun University of Technology,Department of Control Engineering,Changchun,China,130012

3. The Second Hospital of Jilin University,Department of Neurosurgery,Changchun,China,130041

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9872150/9872152/09872282.pdf?arnumber=9872282

Reference33 articles.

1. A CNN-Based Method for Intent Recognition Using Inertial Measurement Units and Intelligent Lower Limb Prosthesis

2. A multi-stream convolutional neural network for sEMG-based gesture recognition in muscle-computer interface

3. sEMG-Based Continuous Estimation of Knee Joint Angle Using Deep Learning with Convolutional Neural Network

4. A CNN-LSTM Hybrid Model for Wrist Kinematics Estimation Using Surface Electromyography

5. Robust and Adaptive Lower Limb Prosthesis Stance Control via Extended Kalman Filter-Based Gait Phase Estimation

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cross-Modality Self-Attention and Fusion-Based Neural Network for Lower Limb Locomotion Mode Recognition;IEEE Transactions on Automation Science and Engineering;2024

2. Toward a Minimal sEMG Setup for Knee and Ankle Kinematic Estimation during Gait;2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS);2023-06

3. A Comparative Study of Joint and Bolt Structures with and without Edge Detection using CNN;2023 International Conference for Advancement in Technology (ICONAT);2023-01-24

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