A method for the classification of finger movements for dexterous control of prosthetic hands
is proposed. Previous research was mainly devoted to identify hand movements as these …

Background Processing and pattern recognition of myoelectric signals have been at the core
of prosthetic control research in the last decade. Although most studies agree on reporting …

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of
EMG signals has been widely used to detect human movement intent, control various …

Different approaches have been proposed to select features and channels for pattern
recognition classification of myoelectric upper-limb prostheses. The goal of this work is to …

Wearable orthoses can function both as assistive devices, which allow the user to live
independently, and as rehabilitation devices, which allow the user to regain use of an …

This contribution presents a novel methodology for myolectric-based control using surface
electromyographic (sEMG) signals recorded during finger movements. A multivariate …

Abstract Convolutional Neural Networks (CNNs) have been subject to extensive attention in
the pattern recognition literature due to unprecedented performance in tasks of information …

Featured Application This work is intended for the development of myoelectric prosthetic
hand systems. Furthermore, the outcome of this study may also benefit other …

This book presents the human hand from an overall perspective–from the first appearance of
hand-like structures in the fins of big fishes living millions of years ago to today ́s and the …

For transradial amputees, the muscles in the residual forearm physiologically used for
flexing/extending the hand fingers are the most appropriate targets for multifingered …