This Paralysed Woman Just Drank A Bottle Of Coffee With Her Mind

This Paralysed Woman Just Drank A Bottle Of Coffee With Her Mind

Our Ghost in the Shell dystopian future will be here sooner than you think. A new study published in Nature today demonstrates for the first time that robotic limbs can successfully be controlled with just the power of the user’s mind.

The study, performed by a team at Brown University and other research institutions, implanted a computer-mind interface about the size of a pea into a patch of neurons in the motor cortexes of two volunteers — a 58-year-old woman and a 66-year-old man, both quadriplegics. This area of the brain is known to activate when moving the extremities, and with a bit of training was able to translate the thoughts and neural activity of the volunteers into physical movement by a remote robotic arm.

Cathy Hutchinson, the female volunteer lost the ability to move her arms and legs after a stroke 15 years ago. However, in this study, she successfully deployed the remote arm to pick up and drink a bottle of coffee without any human intervention — the first time she’s been able to do so in nearly two decades.

As per the study’s synopsis:

Here we demonstrate the ability of two people with long-standing tetraplegia to use neural interface system-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm and hand over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor 5 years earlier, also used a robotic arm to drink coffee from a bottle. Although robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after injury to the central nervous system, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals.

[Nature via NYT]