Researchers have been working to make mind-controlled prosthetics a reality for at least a decade. In theory, an artificial hand that amputees could control with their mind could restore their ability to carry out all sorts of daily tasks, and dramatically improve their standard of living.
However, until now scientists have faced a major barrier: they haven 't been able to access nerve signals that are strong or stable enough to send to the bionic limb. Although it’s possible to get this sort of signal using a brain-machine interface, the procedure to implant one is invasive and costly. And the nerve signals carried by the peripheral nerves that fan out from the brain and spinal cord are too small.
A new implant gets around this problem by using machine learning to amplify these signals. A study, published in Science Translational Medicine today, found that it worked for four amputees for almost a year. It gave them fine control of their prosthetic hands and let them pick up miniature play bricks, grasp items like soda cans, and play the Rock-Paper-Scissors game.
It's the first time researchers have recorded millivolt signals from a nerve-far stronger than any previous study. The strength of this signal allowed the researchers to train algorithms to translate them into movements. “The first time we switched it on, it worked immediately," says Paul Cederna, a biomechanics professor at the University of Michigan, who co-led the study. “There was no gap between thought and movement.”
What is this passage mainly about?
Researchers have been working to make mind-controlled prosthetics a reality for at least a decade. In theory, an artificial hand that amputees could control with their mind could restore their ability to carry out all sorts of daily tasks, and dramatically improve their standard of living.
However, until now scientists have faced a major barrier: they haven 't been able to access nerve signals that are strong or stable enough to send to the bionic limb. Although it’s possible to get this sort of signal using a brain-machine interface, the procedure to implant one is invasive and costly. And the nerve signals carried by the peripheral nerves that fan out from the brain and spinal cord are too small.
A new implant gets around this problem by using machine learning to amplify these signals. A study, published in Science Translational Medicine today, found that it worked for four amputees for almost a year. It gave them fine control of their prosthetic hands and let them pick up miniature play bricks, grasp items like soda cans, and play the Rock-Paper-Scissors game.
It's the first time researchers have recorded millivolt signals from a nerve-far stronger than any previous study. The strength of this signal allowed the researchers to train algorithms to translate them into movements. “The first time we switched it on, it worked immediately," says Paul Cederna, a biomechanics professor at the University of Michigan, who co-led the study. “There was no gap between thought and movement.”
Which of the following will most likely benefit from the research mentioned in the passage?
Researchers have been working to make mind-controlled prosthetics a reality for at least a decade. In theory, an artificial hand that amputees could control with their mind could restore their ability to carry out all sorts of daily tasks, and dramatically improve their standard of living.
However, until now scientists have faced a major barrier: they haven 't been able to access nerve signals that are strong or stable enough to send to the bionic limb. Although it’s possible to get this sort of signal using a brain-machine interface, the procedure to implant one is invasive and costly. And the nerve signals carried by the peripheral nerves that fan out from the brain and spinal cord are too small.
A new implant gets around this problem by using machine learning to amplify these signals. A study, published in Science Translational Medicine today, found that it worked for four amputees for almost a year. It gave them fine control of their prosthetic hands and let them pick up miniature play bricks, grasp items like soda cans, and play the Rock-Paper-Scissors game.
It's the first time researchers have recorded millivolt signals from a nerve-far stronger than any previous study. The strength of this signal allowed the researchers to train algorithms to translate them into movements. “The first time we switched it on, it worked immediately," says Paul Cederna, a biomechanics professor at the University of Michigan, who co-led the study. “There was no gap between thought and movement.”
All the following words can be used interchangeably in the passage except for
Researchers have been working to make mind-controlled prosthetics a reality for at least a decade. In theory, an artificial hand that amputees could control with their mind could restore their ability to carry out all sorts of daily tasks, and dramatically improve their standard of living.
However, until now scientists have faced a major barrier: they haven 't been able to access nerve signals that are strong or stable enough to send to the bionic limb. Although it’s possible to get this sort of signal using a brain-machine interface, the procedure to implant one is invasive and costly. And the nerve signals carried by the peripheral nerves that fan out from the brain and spinal cord are too small.
A new implant gets around this problem by using machine learning to amplify these signals. A study, published in Science Translational Medicine today, found that it worked for four amputees for almost a year. It gave them fine control of their prosthetic hands and let them pick up miniature play bricks, grasp items like soda cans, and play the Rock-Paper-Scissors game.
It's the first time researchers have recorded millivolt signals from a nerve-far stronger than any previous study. The strength of this signal allowed the researchers to train algorithms to translate them into movements. “The first time we switched it on, it worked immediately," says Paul Cederna, a biomechanics professor at the University of Michigan, who co-led the study. “There was no gap between thought and movement.”
According to the passage,which of the following is true?
A
Mind-controlled bionic limbs have been used for at least 50 years.
B
Patients with a mind-controlled prosthesis have to carry a mainframe computer with them.
C
A new implant using machine learning can give amputees control over their prosthetic hands.
D
The artificial hand using the brain-machine interface involves no surgery, and therefore is very cheap.
Researchers have been working to make mind-controlled prosthetics a reality for at least a decade. In theory, an artificial hand that amputees could control with their mind could restore their ability to carry out all sorts of daily tasks, and dramatically improve their standard of living.
However, until now scientists have faced a major barrier: they haven 't been able to access nerve signals that are strong or stable enough to send to the bionic limb. Although it’s possible to get this sort of signal using a brain-machine interface, the procedure to implant one is invasive and costly. And the nerve signals carried by the peripheral nerves that fan out from the brain and spinal cord are too small.
A new implant gets around this problem by using machine learning to amplify these signals. A study, published in Science Translational Medicine today, found that it worked for four amputees for almost a year. It gave them fine control of their prosthetic hands and let them pick up miniature play bricks, grasp items like soda cans, and play the Rock-Paper-Scissors game.
It's the first time researchers have recorded millivolt signals from a nerve-far stronger than any previous study. The strength of this signal allowed the researchers to train algorithms to translate them into movements. “The first time we switched it on, it worked immediately," says Paul Cederna, a biomechanics professor at the University of Michigan, who co-led the study. “There was no gap between thought and movement.”
The paragraph following the passage most likely discusses
A
how a mind-controlled prosthesis works.
B
why amputees want to protest prosthetics.
C
whether the brain-machine interface will change the way we live.
D
the possibility that robots can carry out all sorts of daily tasks in the near future.
Bill Gates,one of the most renowned and respected billionaires worldwide，has donated of money to Bill and Melinda Gates Foundation to reduce global poverty.
