Interferences in the form of white Gaussian noise (WGN) are inevitable during long-term
electromyogram (EMG) recordings. Even with the aid of advanced signal denoising …

Objective. This study investigates the effect of the involuntary motor activity of paretic-spastic
muscles on the classification of surface electromyography (EMG) signals. Approach. Two …

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 …

Simultaneous implementation of myoelectric pattern recognition and muscle force estimation
is highly demanded in building natural gestural interfaces but a challenging task due to the …

Traditional myoelectric prostheses that employ a static pattern recognition model to identify
human movement intention from surface electromyography (sEMG) signals hardly adapt to …

Myoelectric pattern-recognition techniques have been developed to infer user's intention of
performing different functional movements. Thus electromyogram (EMG) can be used as …

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 …

Background Processing the surface electromyogram (sEMG) to decode movement intent is a
promising approach for natural control of upper extremity prostheses. To this end, this paper …

Advances in myoelectric interfaces have increased the use of wearable prosthetics including
robotic arms. Although promising results have been achieved with pattern recognition-based …

Robot-assisted training provides an effective approach to neurological injury rehabilitation.
To meet the challenge of hand rehabilitation after neurological injuries, this study presents …