Upper limb amputation is a condition that significantly restricts the amputees from performing
their daily activities. The myoelectric prosthesis, using signals from residual stump muscles …

Stroke is one of the main causes of long-term disability worldwide, placing a large burden on
individuals and society. Rehabilitation after stroke consists of an iterative process involving …

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

Natural control methods based on surface electromyography (sEMG) and pattern
recognition are promising for hand prosthetics. However, the control robustness offered by …

Hand prostheses controlled by surface electromyography are promising due to the non-
invasive approach and the control capabilities offered by machine learning. Nevertheless …

Recent advances in rehabilitation robotics suggest that it may be possible for hand-
amputated subjects to recover at least a significant part of the lost hand functionality. The …

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

Hand movement classification based on surface electromyography (sEMG) pattern
recognition is a promising approach for upper limb neuroprosthetic control. However …

Electromyography (EMG) signals are becoming increasingly important in many applications,
including clinical/biomedical, prosthesis or rehabilitation devices, human machine …

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