The increasing amount of data in electromyographic (EMG) signal research has greatly
increased the importance of developing advanced data analysis and machine learning …

Upper-limb amputation imposes significant burden on amputees thereby restricting them
from fully exploring their environments during activities of daily living. The use of intelligent …

Wearable devices that monitor muscle activity based on surface electromyography could be
of use in the development of hand gesture recognition applications. Such devices typically …

Specialized myoelectric sensors have been used in prosthetics for decades, but, with recent
advancements in wearable sensors, wireless communication and embedded technologies …

Pattern recognition of electromyography (EMG) signals can potentially improve the
performance of myoelectric control for upper limb prostheses with respect to current clinical …

Objective. Deep learning models can learn representations of data that extract useful
information in order to perform prediction without feature engineering. In this paper, an …

Despite a historical focus on prosthetics, the incorporation of electromyography (EMG)
sensors into less obtrusive wearable designs has recently gained attention as a potential …

We provide a short introduction to the field of topological data analysis (TDA) and discuss its
possible relevance for the study of complex systems. TDA provides a set of tools to …

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

Existing research on myoelectric control systems primarily focuses on extracting
discriminative characteristics of the electromyographic (EMG) signal by designing …