
A computer reads and predicts thoughts
Researchers at the University of Helsinki have developed a technique in which a computer models visual perception by monitoring human brain signals.
Researchers at the University of Helsinki have developed a technique in which a computer models visual perception by monitoring human brain signals.
Linking the human brain to a computer is usually only seen in science fiction, but now scientists have harnessed the power of 3D printing to bring the technology one step closer to reality.
Researchers have developed a revolutionary cortical vision device that could one day help restore vision to the blind.
Researchers have shown that machine learning techniques helped an individual with paralysis learn to control a computer cursor using their brain activity.
Researchers have been working to advance a technology that could one day help people with paralysis regain use of their limbs, and enable amputees to use their thoughts to control prostheses.
Scientists used brain-computer-interface to train the brains of patients to reduce phantom-hand pain.
Scientists have proposed the concept of a memristive neurohybrid chip to be used in compact biosensors and neuroprostheses.
Machine learning will drastically improve brain-computer interfaces and their ability to remain stabilized during use, greatly reducing or potentially eliminating the need to recalibrate these devices.
Next-generation brain implants with more than a thousand electrodes can survive for more than six years.
New prosthetic technologies that stimulate the nerves could pave the way for prostheses that feel like a natural part of the body and reduce the phantom limb pain commonly endured by amputees.
Researchers have tapped faint, latent signals from arm nerves and amplified them to enable real-time, intuitive, finger-level control of a robotic hand.
Researchers have developed advanced brain-computer interface technology that harnesses machine learning to personalise brain-training for children with ADHD.
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.
New research has provided preliminary evidence that training time can be shortened & that user performance tends to improve within a relatively short period of time.
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.
Scientists have developed a miniaturized electronic platform for the stimulation and recording of peripheral nerve fibers-on-a-chip.
Neuroscience researchers University of Chicago receive $3.4 million NIH grant to develop brain-controlled prosthetic limbs.
An engineer is leading a team of researchers, health care providers and industry to fast-track the commercialization of a groundbreaking robotic rehabilitation system.
Engineers use deep learning to decode the conversation between brain and arm, by analyzing electrical patterns in the motor control areas of the brain.
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.