Two years ago, a quadriplegic woman underwent surgery to be fitted with two quarter-inch electrode grids, each fitted with 96 tiny contact points, in the regions of the brain that were responsible for right arm and hand movements. After the electrode grids in the woman’s brain were connected to a computer, creating a brain-machine interface, the 96 individual contact points picked up pulses of electricity that were fired between the neurons in her brain. Computer algorithms were used to decode these firing signals and identify the patterns associated with a particular arm movement, such as raising the arm or turning the wrist. By simply thinking of controlling her arm movements, the patient was then able to make the robotic arm reach out to objects, as well as move it in a number of directions and flex and rotate the wrist. It also enabled Jan to “high five” the researchers. Now, she is able to successfully maneuver the robotic arm in a further four dimensions through a number of hand movements, allowing for more detailed interaction with objects. The study authors report that: “Our results show that individual motor cortical neurons encode many parameters of movement that object interaction is an important factor when extracting these signals, and that high-dimensional operation of prosthetic devices can be achieved with simple decoding algorithms.”
Mind-Controlled Robotic Arm Restores Natural Movements
B Wodlinger, J E Downey, E C Tyler-Kabara, A B Schwartz, M L Boninger, J L Collinger. Ten-dimensional anthropomorphic arm control in a human brain−machine interface: difficulties, solutions, and limitations. Journal of Neural Engineering, 2015; 12 (
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