Researchers have developed a new brain-machine interface headset that harnesses the power of machine learning to allow those with disabilities to maneuver their wheelchair with thought alone.
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··8 min readUsing ECoG and machine learning, researchers decoded spoken words and phrases in real-time from brain signals that control speech. The technology could eventually be used to help those who have lost vocal control to regain their voice.
A new brain-machine interface technology can enhance emotional interaction with music.
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··5 min readUsing EEG and brain computer interface technology, researchers have created a robotic arm that can be controlled without brain implants.
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Findings allow for the development of an autonomously updating brain-machine interface, which is able to improve on its own by learning about its subject without additional programming. The system could help develop new robotic prosthetics, which can perform more naturally.
Learning a new skill may involve the generation of new neural activity patterns.
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A minimally invasive brain implant is to be tested on humans for the first time. The device, named Stentrode, will be placed in blood vessels in the motor cortex, and researchers believe it will help improve movement and speech for those with a range of neurological disorders.
Researchers discuss the potential of deep brain stimulation in the treatment of Parkinson's disease, OCD, Tourette syndrome and other disorders.
Neurofeedback can be used to modify a person's state of arousal in order to improve performance in sensory motor tasks, biomedical engineers report.
Asking participants to bungee jump helps researchers measure Bereitschaftspotential, or readiness potential, outside the lab setting. Researchers say their findings will help in the development of BCIs to assist quadriplegics to control neuroprosthetics.
Researchers report a brain computer interface can enable those with paralysis to directly operate tablet technology just by thinking about cursor movements and clicks.
Study shows pilots in real flight conditions made more errors and had higher anterior prefrontal cortex activation than those who were placed in a simulator, when completing cognitively demanding tasks.