Classification of sEMG Biomedical Signals for Upper-Limb and Hand Rehabilitation Using a Hybrid CNN-SVM Architecture-Reference-Cited by-同舟云学术

Classification of sEMG Biomedical Signals for Upper-Limb and Hand Rehabilitation Using a Hybrid CNN-SVM Architecture

Published:2022-10-25 Issue: Volume: Page:
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Container-title:2022 International Conference on Data Analytics for Business and Industry (ICDABI)
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Author:

Briouza Sami¹,Gritli Hassene²,Khraief Nahla³,Belghith Safya³,Singh Dilbag⁴

Affiliation:

1. University of Tunis El Manar,Laboratory of Robotics, Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis,Le Belvédère,Tunis,Tunisia,1002

2. University of Carthage,Higher Institute of Information and Communication Technologies,Borj Cedria,Tunis,Tunisia,1164

3. University of Tunis El Manar,RISC Lab (LR16ES07) National Engineering School of Tunis,Le Belvédère,Tunis,Tunisia,1002

4. Gwangju Institute of Science and Technology,School of Electrical Engineering and Computer Science,Gwangju,South Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10041434/10041254/10041524.pdf?arnumber=10041524

Reference27 articles.

1. Epileptic Seizure Detection Based on EEG Signals and CNN

2. Classification of sEMG Biomedical Signals for Upper-Limb Rehabilitation Using the Random Forest Method

3. A review on transfer learning in EEG signal analysis

4. EEG dataset classification using CNN method

5. sEMG feature selection and classification using SVM-RFE

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