Virtual reality (VR) and augmented reality (AR) are engaging interfaces that can be of benefit
for rehabilitation therapy. However, they are still not widely used, and the use of surface …

In muscle-computer interface (MCI), deep learning is a promising technology to build-up
classifiers for recognizing gestures from surface electromyography (sEMG) signals …

Training with “Extended Reality” or X-Reality (XR) systems can undoubtedly enhance the
control of the myoelectric prostheses. However, there is no consensus on which factors …

In the field of human-machine interaction, gesture recognition using sparse multichannel
surface electromyography (sEMG) remains a challenge. Based on the Hilbert filling curve, a …

Serious games show a lot of potential for use in movement rehabilitation (eg, after a stroke,
injury to the spinal cord, or limb loss). However, the nature of this research leads to diversity …

Electromyography (EMG) enables hands-free interactions by detecting muscle activity at
different human body locations. Previous studies have demonstrated that input performance …

Using biosignals through electromyography (EMG) and rendering them as feedback for
hands-free interaction finally migrates to engaging virtual reality (VR) experiences for health …

With the development of signal analysis technology and artificial intelligence, surface
electromyography (sEMG) signal gesture recognition is widely used in rehabilitation therapy …

For many applications, hand gesture recognition systems that rely on biosignal data
exclusively are mandatory. Usually, theses systems have to be affordable, reliable as well as …

Research in human–robot interaction for assistive robotics usually presents many technical
challenges for experimenters, forcing researchers to split their time between solving …