This Perspective examines the status of large-scale cortical interfaces through the lens of
potential applications to active implants for brain-machine interfaces. Examples of research …

Decoding behavior, perception or cognitive state directly from neural signals is critical for
brain–computer interface research and an important tool for systems neuroscience. In the …

Objective. To evaluate the potential of intracortical electrode array signals for brain-computer
interfaces (BCIs) to restore lost speech, we measured the performance of decoders trained …

Abstract Brain-Machine Interface systems (BMIs) are clinically valuable devices that can
provide functional restoration for patients with spinal cord injury or improved integration for …

Objective. Steady-state visual evoked potential (SSVEP) is an important control method of
the brain–computer interface (BCI) system. The development of an efficient SSVEP feature …

Steady-state visual evoked potential (SSVEP) signal collected from the scalp typically
contains other types of electric signals, and it is important to remove these noise …

Introduction As an important human-computer interaction technology, steady-state visual
evoked potential (SSVEP) plays a key role in the application of brain computer interface …

Objective. Translational efforts on spike-signal-based implantable brain-machine interfaces
(BMIs) are increasingly aiming to minimise bandwidth while maintaining decoding …

People who have lost the ability to speak due to neurological injuries would greatly benefit
from assistive technology that provides a fast, intuitive, and naturalistic means of …

Objective. Steady-state visual evoked potential (SSVEP) training feature recognition
algorithms utilize user training data to reduce the interference of spontaneous …