In recent years, myoelectric control systems have emerged for upper limb wearable robotic
exoskeletons to provide movement assistance and/or to restore motor functions in people …

Currently, research on gesture recognition systems has been on the rise due to the
capabilities these systems provide to the field of human–machine interaction, however …

Rehabilitation and assistance exoskeletons have been widely studied because they allow to
provide more effective, intensive, and adaptive therapies; in addition, they can be used to …

In the field of noncontact human‐computer interaction, it is of crucial importance to
distinguish different surface electromyography (sEMG) gestures accurately for intelligent …

Hand prosthesis controlled by surface electromyography (sEMG) is promising due to the
control capabilities and the noninvasive technique that machine learning (ML) offers to help …

Myoelectric pattern recognition is widely used to control upper limb prostheses. However,
the non-stationary characteristics of electromyography (EMG) signals, caused by …

sEMG-based gesture recognition is widely applied in human-machine interaction system by
its unique advantages. However, the accuracy of recognition drops significantly as …

Current surface electromyography (sEMG)-based gesture recognition only extracts time or
frequency features from raw sEMG signals, and then puts the features together to generate …

One of the most significant tools for Human–Computer Interaction (HCI) is body language,
namely gestures. Therefore, Gesture recognition using Mechanomyography (MMG) for …

Surface electromyography (sEMG)-based gesture classification is promising in many
emerging applications such as prosthetic control and Augmented Reality (AR)/Virtual Reality …