A newly developed machine learning model can predict the words a person is about to speak based on their neural activity recorded by a minimally invasive neuroprosthetic device.
Feed-forward neural networks improve speed and provide more accurate control of brain-controlled prosthetic hands and fingers.
New findings about neural activity in the sensorimotor cortex may aid in the development of neuroprosthetics to help compensate for neuronal dysfunctions.
Researchers have developed a new, fully automated prosthetic arm that learns during normal use and adapts to varying conditions.
An innovative new clinical trial seeks to explore how the brain adapts to bionic arms in children born without limbs. The study aims to improve prosthetics mastery in children.
Researchers have developed a novel hybrid machine learning approach to muscle gesture recognition in prosthetic arms.
Researchers created a form of artificial vision for a blind woman with the aid of a brain implant position in the visual cortex. The results pave the way for the creation of visual brain prosthetics to help the blind to regain sight.
A newly developed bionic arm combines motor control with touch and hand movement sensations, allowing those with upper-arm amputations to behave and react as though they haven't lost their limb.
Using magnetic beads implanted into muscle tissue within the amputated residuum of animals, researchers have created a more precise way to control prosthetic limbs.
MIT researchers have developed a new, lightweight robotic hand that provides tactile feedback and is dexterous enough to perform tasks like zipping a suitcase and pouring juice.
"Neurograins" brain-computer interfaces independently record electrical impulses and send signals wirelessly to a central hub that coordinates and processes the signals.
A new touch-sensing glove can feel pressure and other tactile stimuli, researchers report. The glove has applications for those with motor function disorders and could be adapted from virtual reality gaming experiences.
