A 4-limb robotic system controlled by brain signals helped a tetraplegic man to move his arms and walk using a ceiling-mounted harness for balance.
Combining new wearable electronics and a deep learning algorithm could help disabled people wirelessly interact with a computer.
Scientists have successfully tested neuroprosthetic technology that combines robotic control with users’ voluntary control, opening avenues in the new interdisciplinary field of shared control for neuroprosthetic technologies.
Machine enhanced humans – or cyborgs as they are known in science fiction – could be one step closer to becoming a reality.
Researchers show that by using a noninvasive brain-computer interface they could control a robotic arm that’s tracking a cursor on a computer screen.
A state-of-the-art brain-machine interface created by UC San Francisco neuroscientists can generate natural-sounding synthetic speech by using brain activity to control a virtual vocal tract – an anatomically detailed computer simulation including the lips, jaw, tongue and larynx.
Researchers have shown that they can use online neurofeedback to modify an individual's arousal state to improve performance in a demanding sensory motor task.
Research from the BrainGate consortium shows that a brain-computer interface (BCI) can enable people with paralysis to directly operate an off-the-shelf tablet device just by thinking about making cursor movements and clicks.
An engineer is leading a team of researchers, health care providers and industry to fast-track the commercialization of a groundbreaking robotic rehabilitation system.
Getting a better grip on things: The MoreGrasp Horizon2020 research project is coming to an end with significant results in the field of thought-controlled grasp neuroprosthetics. A large-scale feasibility study is underway.