From Unstable Electrode Contacts to Reliable Control: A Deep Learning Approach for HD-sEMG in Neurorobotics-Reference-Cited by-同舟云学术

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From Unstable Electrode Contacts to Reliable Control: A Deep Learning Approach for HD-sEMG in Neurorobotics

Published:2024-05-13 Issue: Volume: Page:7874-7879
ISSN:
Container-title:2024 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Tyacke Eion¹,Gupta Kunal²,Patel Jay²,Katoch Raghav²,Atashzar S. Farokh²

Affiliation:

1. Carnegie Mellon University

2. New York University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609961/10609862/10610638.pdf?arnumber=10610638

Reference24 articles.

1. A Review of Myoelectric Control for Prosthetic Hand Manipulation

2. Optimization of HD-sEMG-Based Cross-Day Hand Gesture Classification by Optimal Feature Extraction and Data Augmentation

3. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

4. Transformer-based hand gesture recognition from instantaneous to fused neural decomposition of high-density EMG signals

5. A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition

Cited by 1 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. ViT-MDHGR: Cross-Day Reliability and Agility in Dynamic Hand Gesture Prediction via HD-sEMG Signal Decoding;IEEE Journal of Selected Topics in Signal Processing;2024-04

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