Recurrent Neural Network as Estimator for a Virtual sEMG Channel

Published: Jul 1, 2019
Abstract
This study aims at estimating a virtual surface Electromyography (sEMG) channel through a Recurrent Neural Network (RNN) by using Long Short-Term Memory (LSTM) nodes. The virtual channel is used to classify hand postures from the publicly NinaPro database with a multi-class, one-against-all Support Vector Machine (SVM) using the Root Mean Square RMS of the sEMG signal as feature. The classification of the signals through the virtual channel was...
Paper Details
Title
Recurrent Neural Network as Estimator for a Virtual sEMG Channel
Published Date
Jul 1, 2019
Journal
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