Active Movements Intention Recognition for Upper Limb Rehabilitation Robots Based on EMG Signals-Reference-Cited by-同舟云学术

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Active Movements Intention Recognition for Upper Limb Rehabilitation Robots Based on EMG Signals

Published:2023-07-17 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Real-time Computing and Robotics (RCAR)
language:
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Author:

Zhang Hengwei¹,Xu Linsen²,Chen Gen¹

Affiliation:

1. Hohai University,School of Mechanical and Electrical Engineering,Changzhou,China,213000

2. Hohai University; Changzhou Key Laboratory of Intelligent Manufacturing Technology and Equipment; Suzhou Research Institute, Hohai University,College of Mechanical and Electrical Engineering,Changzhou,China,213000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10249208/10249018/10249909.pdf?arnumber=10249909

Reference21 articles.

1. Deep learning approach to control of prosthetic hands with electromyography signals

2. Surface EMG signal classification using ternary pattern and discrete wavelet transform based feature extraction for hand movement recognition

3. Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands[J];manfredo;Front Neurorobot,2016

4. A convolutional neural network for robotic arm guidance using sEMG based frequency-features[C];allard;2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),2016

5. Light-weighted CNN-Attention based architecture for Hand Gesture Recognition via ElectroMyography[J];zabihi,2022

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