GPU has emerged as the go-to accelerator for HPC workloads, however its power
consumption has become a major limiting factor for further scaling HPC systems. An …

Motion intent recognition for controlling prosthetic systems has long relied on machine
learning algorithms. Artificial neural networks have shown great promise for solving such …

Introduction Myoelectric control of prostheses is a long-established technique, using surface
electromyography (sEMG) to detect user intention and perform subsequent mechanical …

Recent advancements in robotic prosthetic hand technology have led to significant progress,
resulting in the development of lighter-weight devices capable of implementing a diverse …

Hand gesture recognition (HGR) has gained significant attention due to the increasing use
of AI-powered human–computer interfaces (HCIs) that can interpret the deep spatiotemporal …

Deep learning models in computer vision have achieved significant success but pose
increasing concerns about energy consumption and sustainability. Despite these concerns …

For users who lost their arms during the work and war, an increasing strong demand of
myoelectrical driven prosthetic system based on surface EMG (sEMG) data and pattern …