Locomo-Net: A Low -Complex Deep Learning Framework for sEMG-Based Hand Movement Recognition for Prosthetic Control

Locomo-Net: A Low -Complex Deep Learning Framework for sEMG-Based Hand Movement Recognition for Prosthetic Control

Background: The enhancement in the performance of the myoelectric pattern recognition techniques based on deep learning algorithm possess computationally expensive and exhibit extensive memory behavior. Therefore, in this paper we report a deep learning framework named `Low-Complex Movement recognit...

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Bibliographic Details
Main Authors: Arvind Gautam, Madhuri Panwar, Archana Wankhede, Sridhar P. Arjunan, Ganesh R. Naik, Amit Acharyya, Dinesh K. Kumar
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
sEMG
movement classification
signal processing
CNN
data compression
weights compression
Online Access:https://ieeexplore.ieee.org/document/9197671/

Internet

https://ieeexplore.ieee.org/document/9197671/

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