A 3DCNN-LSTM Hybrid Framework for sEMG-Based Noises Recognition in Exercise

A 3DCNN-LSTM Hybrid Framework for sEMG-Based Noises Recognition in Exercise

Recently, surface electromyography (sEMG) has been used to detect running-related works. sEMG provides a non-invasive and real-time method that allows quantification of muscle energy. However, noises in sEMG signals are a serious issue to be considered as these will interrupt the analysis of muscula...

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Bibliographic Details
Main Authors: Min-Wen Lin, Shanq-Jang Ruan, Ya-Wen Tu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Data-augmentation
deep learning
long short-term memory
sEMG
sEMG noises
3D convolution neural network
Online Access:https://ieeexplore.ieee.org/document/9184899/

Internet

https://ieeexplore.ieee.org/document/9184899/

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