Wearables developed for human body signal detection receive increasing attention in the
current decade. Compared to implantable sensors, wearables are more focused on body …

Gesture recognition technology is widely used in the flexible and precise control of
manipulators in the assisted medical field. Our MResLSTM algorithm can effectively perform …

To improve the classification accuracy of hand movements from sEMG signals, this paper
puts forward a unified hand gesture classification framework which exploits the potentials of …

In clinical practice, acute post-stroke paresis of the extremities fundamentally complicates
timely rehabilitation of motor functions; however, recently, residual and distorted …

Despite achieving accuracies higher than 90% on recognizing upper-limb movements
through sEMG (surface Electromyography) signal with the state of art classifiers in the …

Flexible metal electrodes are essential for flexible electronics, where the main challenge is
to obtain mask-free patterned metals directly on substrates such as poly (dimethylsiloxane) …

The performance of a robotic exoskeleton depends upon the accuracy of control commands
from the controller fed with Surface ElectroMyoGraphy (sEMG) input signals. The …

Surface electromyography (sEMG) is a non-invasive and straightforward way to allow the
user to actively control the prosthesis. However, results reported by previous studies on …

In this article, to reduce the complexity and improve the generalization ability of current
gesture recognition systems, we propose a novel SE-CNN attention architecture for sEMG …

Inspired by the biological behavior of domestic cats, the Cat Swarm Optimization (CSO) is a
metaheuristic which has been successfully applied to solve several optimization problems …