In recent years, there has been major interest in the exposure to physical therapy during
rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and …

The surface electromyography (sEMG) records the electrical activity of muscle fibers during
contraction: one of its uses is to assess changes taking place within muscles in the course of …

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

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 …

In pattern recognition-based myoelectric control, high accuracy for multiple discriminated
motions is presented in most of related literature. However, there is a gap between the …

In recent years, the detection of voluntary motor intentions from electroencephalogram
(EEG) has been used for triggering external devices in closed-loop brain–computer interface …

Spinal cord injury (SCI) and stroke are pathologies that often result in the loss of/decrease in
hand functionality. Hand function is a critical component of everyday life and therefore, a …

Electromyography (EMG) signals are instrumental in a variety of applications including
prosthetic control, muscle health assessment, rehabilitation, and workplace monitoring …

Exercise fatigue is a common physiological phenomenon in human activities. The
occurrence of exercise fatigue can reduce human power output and exercise performance …

The extraction of the accurate and efficient descriptors of muscular activity plays an
important role in tackling the challenging problem of myoelectric control of powered …