Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
Author:
Affiliation:
1. Riphah International University,Department of Biomedical Engineering,Lahore,Pakistan,54000
2. Riphah International University,Department of Electrical Engineering,Islamabad,Pakistan,44000
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10007062/10007091/10007103.pdf?arnumber=10007103
Reference20 articles.
1. A hybrid approach to product prototype usability testing based on surface EMG images and convolutional neural network classification
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1. Motion intention recognition of the affected hand based on the sEMG and improved DenseNet network;Heliyon;2024-03
2. EMG gesture signal analysis towards diagnosis of upper limb using dual-pathway convolutional neural network;Mathematical Biosciences and Engineering;2024
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