This paper reviews the state of the arts and trends of the AI-Based biomedical processing
algorithms and hardware. The algorithms and hardware for different biomedical applications …

Surface electromyography (sEMG) is a non-invasive method of measuring neuromuscular
potentials generated when the brain instructs the body to perform both fine and coarse …

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 …

Hands are two of the most crucial organs and they play major role for human activities.
Therefore, amputee people experience many difficulties in daily life. To overcome these …

This work is motivated by the recent advances in Deep Neural Networks (DNNs) and their
widespread applications in human-machine interfaces. DNNs have been recently used for …

Background Myoelectric pattern recognition systems can decode movement intention to
drive upper-limb prostheses. Despite recent advances in academic research, the …

Hand amputation can dramatically affect the capabilities of a person. Cortical reorganization
occurs in the brain, but the motor and somatosensorial cortex can interact with the remnant …

Electromyography (EMG) is a technique for recording biomedical electrical signals obtained
from the neuromuscular activities. These signals are used to monitor medical abnormalities …