Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

Amputation of the upper limb brings heavy burden to amputees, reduces their quality of life,
and limits their performance in activities of daily life. The realization of natural control for …

Thanks to the powerful capability of the feature extraction, deep learning has become a
promising technology for an increasing number of researchers to decode movements from …

In this study, a three-dimensional (3D) printed soft robotic hand with embedded soft sensors,
intended for prosthetic applications is designed and developed to efficiently operate with …

This letter investigates the feasibility of a generalizable solution for human-robot interfaces
through peripheral multichannel Electromyography (EMG) recording. We propose a …

Recently, there has been a surge of significant interest on application of Deep Learning (DL)
models to autonomously perform hand gesture recognition using surface Electromyogram …

The spectrotemporal information content of surface electromyography has shown strong
potential in predicting the intended motor command. During the last decade, with …

The development of alternative pathways to communicate with outside world independent
on language or limb motions is important. However, one of the challenges is the multi …

Background & purpose For the best possible outcomes from therapy, proximal femur bone
cancers must be accurately classified. This work creates an artificial intelligence (AI) model …

Deep networks have been recently proposed to estimate motor intention using conventional
bipolar surface electromyography (sEMG) signals for myoelectric control of neurorobots. In …