Posted by: devnullius
« on: 28. September 2013., 09:10:48 »
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Posted by: Samker
« on: 27. September 2013., 19:14:40 »Fantastic! 
Posted by: devnullius
« on: 27. September 2013., 15:08:59 »Copy Paste FROM: http://www.newscientist.com/article/dn24265-man-controls-new-prosthetic-leg-using-thought-alone.html#
Video: Man controls robotic leg using thoughts alone (http://www.youtube.com/watch?v=nGmIS9YeuuQ)
A man missing his lower leg has gained precise control over a prosthetic limb, just by thinking about moving it – all because his unused nerves were preserved during the amputation and rerouted to his thigh where they can be used to communicate with a robotic leg.
The man can now seamlessly switch from walking on level ground to climbing stairs and can even kick a football around.
During a traditional limb amputation, the main sensory nerves are severed and lose their function. In 2006, Todd Kuiken and his colleagues at the Rehabilitation Institute of Chicago in Illinois realised they could preserve some of that functionality by carefully rerouting sensory nerves during an amputation and attaching them to another part of the body.
They could then use the rerouted nerve signals to control a robotic limb, allowing a person to control their prosthesis with the same nerves they originally used to control their real limb.
Kuiken's team first attempted the procedure – which is called targeted muscle reinnervation (TMR) – on people who were having their arm amputated. Now, Kuiken's team has performed TMR for the first time on a man with a leg amputation.
Taking a different route
First, the team rerouted the two main branches of the man's sciatic nerve to muscles in the thigh above the amputation. One branch controls the calf and some foot muscles, the other controls the muscle running down the outside leg and some more foot muscles.
After a few months, the man could control his thigh muscles by thinking about using his missing leg. The next step was to link up a prosthesis.
The robot leg in question is a sophisticated prosthesis: it carries a number of mechanical sensors including gyroscopes and accelerometers, and can be trained to use the information from these sensors to perform certain walking styles. Kuiken's team reckoned that the leg would perform even better if it could infer the user's intended walking style with information from the sciatic nerve.
To do so, the researchers asked their volunteer to attempt to perform certain movements with his missing leg – for instance, flexing the foot – while they monitored the pattern of electric signals from the rerouted nerves in the thigh muscles. The researchers then programmed the robot leg to flex its foot whenever it detected that particular pattern of electrical activity.
Using just the mechanical sensor data, the robotic leg made the correct movement about 87 per cent of the time. With additional data from the nerves, the success rate rose to 98 per cent, and there were no so-called critical errors – errors that increase the risk of the user losing balance and falling. Those kinds of errors are most common when the user suddenly shifts walking style – when they begin to climb stairs, for instance, but with the additional information from the nerves, the robotic leg can make a seamless, natural transition between walking styles (see video).
"I think this kind of work is very important," says Michael Goldfarb at Vanderbilt University in Nashville, Tennessee, who helped design the robot leg.
"There's a lot you can do with physical sensors but at some point you really need to know the user's intent – when they want to change from running, to walking, to stair climbing," says Goldfarb. "These electrical signals give you an extra set of information to work on.
"This new generation of robotic legs are much more capable than anything that's come before. They can pretty much do whatever the healthy limb can do," he says.
Journal reference: New England Journal of Medicine, DOI: 10.1056/nejmoa1300126 (http://dx.doi.org/10.1056/nejmoa1300126)
... Karma!
Devvie
~~~ notemail@facebook.com ~~~
Conare nullius momenti videri fortasse missilibus careant
——
All spelling mistakes are my own and may only be distributed under the GNU General Public License! – (© 95-1 by Coredump; 2-013 by DevNullius)
Video: Man controls robotic leg using thoughts alone (http://www.youtube.com/watch?v=nGmIS9YeuuQ)
A man missing his lower leg has gained precise control over a prosthetic limb, just by thinking about moving it – all because his unused nerves were preserved during the amputation and rerouted to his thigh where they can be used to communicate with a robotic leg.
The man can now seamlessly switch from walking on level ground to climbing stairs and can even kick a football around.
During a traditional limb amputation, the main sensory nerves are severed and lose their function. In 2006, Todd Kuiken and his colleagues at the Rehabilitation Institute of Chicago in Illinois realised they could preserve some of that functionality by carefully rerouting sensory nerves during an amputation and attaching them to another part of the body.
They could then use the rerouted nerve signals to control a robotic limb, allowing a person to control their prosthesis with the same nerves they originally used to control their real limb.
Kuiken's team first attempted the procedure – which is called targeted muscle reinnervation (TMR) – on people who were having their arm amputated. Now, Kuiken's team has performed TMR for the first time on a man with a leg amputation.
Taking a different route
First, the team rerouted the two main branches of the man's sciatic nerve to muscles in the thigh above the amputation. One branch controls the calf and some foot muscles, the other controls the muscle running down the outside leg and some more foot muscles.
After a few months, the man could control his thigh muscles by thinking about using his missing leg. The next step was to link up a prosthesis.
The robot leg in question is a sophisticated prosthesis: it carries a number of mechanical sensors including gyroscopes and accelerometers, and can be trained to use the information from these sensors to perform certain walking styles. Kuiken's team reckoned that the leg would perform even better if it could infer the user's intended walking style with information from the sciatic nerve.
To do so, the researchers asked their volunteer to attempt to perform certain movements with his missing leg – for instance, flexing the foot – while they monitored the pattern of electric signals from the rerouted nerves in the thigh muscles. The researchers then programmed the robot leg to flex its foot whenever it detected that particular pattern of electrical activity.
Using just the mechanical sensor data, the robotic leg made the correct movement about 87 per cent of the time. With additional data from the nerves, the success rate rose to 98 per cent, and there were no so-called critical errors – errors that increase the risk of the user losing balance and falling. Those kinds of errors are most common when the user suddenly shifts walking style – when they begin to climb stairs, for instance, but with the additional information from the nerves, the robotic leg can make a seamless, natural transition between walking styles (see video).
"I think this kind of work is very important," says Michael Goldfarb at Vanderbilt University in Nashville, Tennessee, who helped design the robot leg.
"There's a lot you can do with physical sensors but at some point you really need to know the user's intent – when they want to change from running, to walking, to stair climbing," says Goldfarb. "These electrical signals give you an extra set of information to work on.
"This new generation of robotic legs are much more capable than anything that's come before. They can pretty much do whatever the healthy limb can do," he says.
Journal reference: New England Journal of Medicine, DOI: 10.1056/nejmoa1300126 (http://dx.doi.org/10.1056/nejmoa1300126)
... Karma!
Devvie
~~~ notemail@facebook.com ~~~
Conare nullius momenti videri fortasse missilibus careant
——
All spelling mistakes are my own and may only be distributed under the GNU General Public License! – (© 95-1 by Coredump; 2-013 by DevNullius)