Implantable brain machine interfaces (BMIs) are now on a trajectory to go mainstream,
wherein what was once considered last resort will progressively become elective at earlier …

One of the major challenges in system neurosciences consists in developing techniques for
estimating the cognitive information content in brain activity. This has an enormous potential …

Bioelectrodes have been developed to efficiently mediate electrical signals of biological
systems as stimulators and recording devices. Recently, conductive hydrogels have …

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 …

Bluetooth-enabled wearables can be linked to form synchronized networks to provide
insightful and representative data that is exceptionally beneficial in healthcare applications …

Background and objective Recognition of motor intention based on electroencephalogram
(EEG) signals has attracted considerable research interest in the field of pattern recognition …

Objective. Complex spatiotemporal neural activity encodes rich information related to
behavior and cognition. Conventional research has focused on neural activity acquired …

The brain-computer interface (BCI)-mediated rehabilitation is emerging as a solution to
restore motor skills in paretic patients after stroke. In the human brain, cortical motor neurons …

In human-machine interfaces (HMI), deep learning (DL) techniques such as convolutional
neural networks (CNN), long-short term memory networks (LSTM) and the hybrid CNN …

SCALO is the first distributed brain-computer interface (BCI) consisting of multiple wireless-
networked implants placed on different brain regions. SCALO unlocks new treatment options …