Today, daily life is composed of many computing systems, therefore interacting with them in
a natural way makes the communication process more comfortable. Human–Computer …

This paper gives an overview of the different research works related to electromyographic
signals (EMG) classification based on Support Vector Machines (SVM). The article …

Gesture recognition in dynamic images is challenging in computer vision, automation and
medical field. Hand gesture tracking and recognition between both human and computer …

In recent years, surface electromyography (sEMG) signals have been increasingly used in
pattern recognition and rehabilitation. In this paper, a real-time hand gesture recognition …

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 …

Researchers have recently focused their attention on vision-based hand gesture
recognition. However, due to several constraints, achieving an effective vision-driven hand …

As the life expectancy of individuals increases with recent advancements in medicine and
quality of living, it is important to monitor the health of patients and healthy individuals on a …

Accurate surface electromyography decoding of hand gestures is pivotal for advancing
human–computer interaction applications. Recent developments in end-to-end deep neural …

Bioelectronics stickers that interface the human epidermis and collect electrophysiological
data will constitute important tools in the future of healthcare. Rapid progress is enabled by …

Electromyography (EMG) is an integral part of many biomedical and healthcare applications.
It has been used as a metric for tracking rehabilitation progress and identifying diseases that …