There is a significant progress in the development of brain-controlled mobile robots and
robotic arms in the recent years. New advances in electroencephalography (EEG) …

Continuous decoding of hand kinematics has been recently explored for the intuitive control
of electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs). Deep neural …

Establishing the basic knowledge, methodology, and technology for a framework for the
continuous decoding of hand/arm movement intention was the aim of the ERC-funded …

We show that persons with spinal cord injury (SCI) retain decodable neural correlates of
attempted arm and hand movements. We investigated hand open, palmar grasp, lateral …

Objective. Continuous decoding of voluntary movement is desirable for closed-loop, natural
control of neuroprostheses. Recent studies showed the possibility to reconstruct the hand …

In this paper, a hybrid-domain deep learning (DL)-based neural system is proposed to
decode hand movement preparation phases from electroencephalographic (EEG) …

While many voluntary movements involve bimanual coordination, few attempts have been
made to simultaneously decode the trajectory of bimanual movements from …

Objective In recent years, motor imagery-based brain–computer interfaces (MI-BCIs) have
developed rapidly due to their great potential in neurological rehabilitation. However, the …

Movement decoders exploit the tuning of neural activity to various movement parameters
with the ultimate goal of controlling end-effector action. Invasive approaches, typically …

Movement preparation and initiation have been shown to involve large scale brain networks.
Recent findings suggest that movement preparation and initiation are represented in …