Surface EMG-based gestures recognition systems are helping the disable to enjoy a better
life. Academic institutes and commercial companies have been developing a lot of sEMG …

This manuscript presents a hybrid study of a comprehensive review and a systematic
(research) analysis. Myoelectric control is the cornerstone of many assistive technologies …

In recent years, deep learning algorithms have become increasingly more prominent for
their unparalleled ability to automatically learn discriminant features from large amounts of …

High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity
from a restricted area of the skin by using two dimensional arrays of closely spaced …

We investigate the problem of achieving robust control of hand prostheses by the
electromyogram (EMG) of transradial amputees in the presence of variable force levels, as …

This work is motivated by the recent advances in Deep Neural Networks (DNNs) and their
widespread applications in human-machine interfaces. DNNs have been recently used for …

Recently, the development of practical myoelectric interfaces has resulted in the emergence
of wearable rehabilitation robots such as arm prosthetics. In this paper, we propose a novel …

Surface electromyography (EMG) is one of the promising signals for the recognition of the
intended hand movement of an amputee. Nevertheless, there are several barriers to its …

Myoelectric control is filled with potential to significantly change human–robot interaction
due to the ability to non-invasively measure human motion intent. However, current control …

Surface Electromyography (EMG)-based pattern recognition methods have been
investigated over the past years as a means of controlling upper limb prostheses. Despite …