Wearable devices that monitor muscle activity based on surface electromyography could be
of use in the development of hand gesture recognition applications. Such devices typically …

Hand movement classification based on surface electromyography (sEMG) pattern
recognition is a promising approach for upper limb neuroprosthetic control. However …

Gesture recognition using sparse multichannel surface electromyography (sEMG) is a
challenging problem, and the solutions are far from optimal from the point of view of muscle …

ABSTRACT A decade ago, a group of researchers from academia and industry identified a
dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis …

Pattern recognition of electromyography (EMG) signals can potentially improve the
performance of myoelectric control for upper limb prostheses with respect to current clinical …

In the field of rehabilitation, the electromyography (EMG) signal plays an important role in
interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the …

This paper presents a real-time fine gesture recognition system for multi-articulating hand
prosthesis control, using an embedded convolutional neural network (CNN) to classify hand …

In this paper, we characterize the Ninapro database and its use as a benchmark for hand
prosthesis evaluation. The database is a publicly available resource that aims to support …