Analyzing the Impact of Varied Window Hyper-parameters on Deep CNN for sEMG based Motion Intent Classification-Reference-Cited by-同舟云学术

Analyzing the Impact of Varied Window Hyper-parameters on Deep CNN for sEMG based Motion Intent Classification

Published:2022-06-07 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)
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Author:

Kulwa Frank¹,Samuel Oluwarotimi Williams¹,Asogbon Mojisola Grace¹,Obe Olumide Olayinka²,Li Guanglin¹

Affiliation:

1. Chinese Academy of Sciences (CAS), Shenzhen Institute of Advanced Technology (SIAT),CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems,Shenzhen,Guangdong,China,518055

2. Federal University of Technology,Department of Computer Science,Akure,Nigeria

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9831192/9831456/09831573.pdf?arnumber=9831573

Reference26 articles.

1. Exploiting the Intertemporal Structure of the Upper-Limb sEMG: Comparisons between an LSTM Network and Cross-Sectional Myoelectric Pattern Recognition Methods

2. FS-HGR: Few-Shot Learning for Hand Gesture Recognition via Electromyography

3. Decoding HD-EMG Signals for Myoelectric Control - How Small Can the Analysis Window Size be?

4. Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands

5. Deep Learning in EMG-based Gesture Recognition

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