(ORDO NEWS) — The Applied Physics Laboratory at Johns Hopkins University, USA, has developed robotic arms that are controlled by the human brain.
A partially paralyzed man was able to cut and eat dessert using a brain-computer interface that controls robotic arms.
If a person cannot eat on his own, it is very difficult for him. But a robot can help
Intelligent robotic systems and brain-machine interfaces are already able to partially restore the functionality and independence of people living with sensorimotor impairments.
But tasks that require coordination of both hands, and subtle, fluid movements, are still extremely difficult.
It’s hard for us to imagine, but one of these tasks is the process of eating. It turns out that we do not even notice how complex the technique is implemented by our hands under the control of the brain.
Pick up a fork and knife. Put them on a plate. Fix, for example, a cake with a fork. Bring up the knife. Cut. And on the fork, accurately (without missing!)
Bring it to your mouth. And this is a very rough description. There are actually many more processes involved, and they are all complex.
Our hands have many degrees of freedom, and in order to implement control, the brain must give commands accurately, and the hands must respond clearly.
Scientists from the Applied Physics Laboratory at Johns Hopkins University, USA, have developed two prostheses – robotic arms and connected them via a brain-computer interface to the brain of a 49-year-old participant in the experiment. His hands do not work due to a partial lesion of the spinal cord.
The patient was given arrays of microelectrodes on the sensorimotor areas of the brain.
The participant gave commands to both robotic arms while trying to eat on their own. Commands from the brain-computer interface were decoded to control each hand simultaneously.
And gradually, the person learned to control the movement of both robotic arms so precisely that he was able to cut and sit down dessert.
This is one of the first demonstrations of coordinated control of two robotic arms via a brain-computer interface.
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