Zero crossings are a practical and efficient feature to approximate the frequency of a
sampled series of data. Some research describes in different ways how to compute the zero …

Despite the technological progress in robotics achieved in the last decades, prosthetic limbs
still lack functionality, reliability, and comfort. Recently, an implanted neuromusculoskeletal …

This article proposes a hardware design of hand gesture recognition and its implementation
on the Zynq platform (XC7Z020) of Xilinx. This proposed system is aimed to be embedded …

The functionality of upper limb prostheses can be improved by intuitive control strategies that
use bioelectric signals measured at the stump level. One such strategy is the decoding of …

Motion intent recognition for controlling prosthetic systems has long relied on machine
learning algorithms. Artificial neural networks have shown great promise for solving such …

Myoelectric control is using electromyography (EMG) signal as a source of control, with this
technique, we can control any computer based system such as robots, devices or even …

Advances in electromyographic (EMG) sensor technology and machine learning algorithms
have led to an increased research effort into high density EMG-based pattern recognition …

The present study introduces a method for detecting possible neuropathy or myopathy cases
of a subject based on surface electromyograms signals; the same method has been …

To the present day, the control of prosthetic mechanisms and the classification of surface
Electro-Myography (sEMG) signals is heavily influenced by multiple factors, such as the …

The combination of high-density electromyographic (HD EMG) sensor technology and
modern machine learning algorithms allows for intuitive and robust prosthesis control of …