Amputation of the upper limb brings heavy burden to amputees, reduces their quality of life,
and limits their performance in activities of daily life. The realization of natural control for …

Fog computing is an architectural style in which network components between devices and
the cloud execute application-specific logic. We present the first review on fog computing …

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 …

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

By training the deep neural network model, the hidden features in Surface
Electromyography (sEMG) signals can be extracted. The motion intention of the human can …

Human activity detection within smart homes is one of the basis of unobtrusive wellness
monitoring of a rapidly aging population in developed countries. Most works in this area use …

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 …

Control algorithms for upper limb myoelectric prostheses have been in development since
the mid-1940s. Despite advances in computing power and in the performance of these …

Wearable devices offer interesting features, such as low cost and user friendliness, but their
use for medical applications is an open research topic, given the limited hardware resources …