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Thousands of people
need better prosthetic limbs.
No one knows how to make them.
by Michael Chorost
PHOTO GRAPHS BY ANDRES SERRANO
100
THE BECKER LOCK GRIP
HAND (MID -1960 S )
through these motions, Lehman imagines his missing arm moving in the same
way. This focused mental exercise triggers
neuromuscular activity in his stump that
the electrodes pick up. A cell phone–sized
computer velcroed onto the sling behind
Lehman’s shoulder correlates the arm’s
vocabulary of motions to Lehman’s desires.
The hand pinches closed, Lehman tries to
tell his missing hand “pinch,” and the computer remembers the muscle activation that
his thought engenders. He has to go through
this routine every time he straps on the arm
because the sensors never end up in exactly
the same place. Lehman’s stump changes
from day to day, too. He sweats. His skin
stretches. His muscles swell and shrink.
And, more fundamentally, Lehman’s brain
changes. Tomorrow he might visualize his
arm movements differently.
Once the training is finished, Lehman
shows off a little. He’s able to grip the small
pull tab on his jacket zipper with the artificial thumb and forefinger and zip it up. He
reaches into a fridge and takes out a plastic
bottle. He even picks up a quarter off a table
and drops it through a slot. Still, his control is far from perfect. It takes several tries
before he’s able to grasp the zipper properly.
He drops the bottle and uses his real arm to
pick it up and put it back in the fridge so he
can try again. He fumbles for the quarter
over and over. Often the arm stops cold for
a few seconds while Lehman stares at it. It’s
These prostheses are also body-powered.
A cable attached to a harness means that
shoulder movements can control the arms.
that uses a computer to read the myoelectric impulses that are produced by the
tiny neural zaps inside muscles. In short,
when Lehman is wearing the new arm, he is
a cyborg. But being a cyborg has not turned
out the way science fiction promised.
Iraqi insurgents lobbed two RKG-3 armorsurgery was excruciating. “Everybody asks,
piercing hand grenades at an up-armored
what was it like?” Lehman says. “The best
Humvee in Baghdad. The first grenade, a answer I have is that it was like having your
dud, bounced off the passenger-side door.
hand slammed in a car door continuously.”
But the second one detonated, sending a
Usually, a veteran like Lehman would
jet of molten copper through the door and
get a prosthetic arm, and life, with luck,
through the right elbow of Sergeant First
would go on. But Lehman’s stump was the
Class Glen Lehman. The liquid metal con- right shape for an experimental surgery
tinued across Lehman’s lap, burning his
called targeted muscle reinnervation. He
right thigh, and then sluiced across his left was game to try, in return for access to a
forearm.
remarkable new prosthetic arm.
The platoon medic was in the Humvee,
Lehman’s surgeons delicately pulled
too, but he couldn’t extract Lehman
apart the nerves in his arm that would
through the shattered door. So the medic
ordinarily control his elbow and hand and
started treatment in the truck, in the moved them. His distal radial nerve, which
dark, amid a mess of blood and smoke
controls opening the hand, went to the latand debris, wriggling around Lehman’s
eral head of his triceps. His median nerve,
6' 4" frame. Twenty minutes later Lehman which controls closing the hand, went to
was at a field hospital. Transferred by heli- the medial head of the biceps.
copter to Joint Base Balad, 40 miles north,
It’s a weird surgery with weird effects;
Lehman received almost seven pints of
Lehman’s skin ripples when he thinks
blood, more than half his body’s volume.
about moving his missing right arm, a
Doctors in Germany had to amputate what
physical reminder of the signals his brain
remained of Lehman’s right arm above is sending. When he tries to close his
the elbow and then transferred him to hand, his biceps contracts. The rerouted
Walter Reed Army Medical
nerves are supposed
Center in Washington, DC.
to improve control of
The aftermath of all that Some prostheses, like the hand on
a new prosthesis, one
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APR 2012
the opening spread, operate with
a control cable: Extend your arm
forward to open the hand.
At the Rehabilitation Institute of Chicago,
a researcher helps Lehman put on his
experimental arm for only the third time.
She slides onto his stump a cloth sleeve
studded with eight pairs of disk-shaped
electrodes that can pick up myoelectric
activity. Then she fits the prosthetic arm
over the sleeve and anchors it to his body
with a sling that wraps around his torso.
The arm is a Frankenstein agglomeration
of off-the-shelf prosthetic parts—the elbow
and forearm come from a company in
Massachusetts. The rotating wrist is from
Germany; the hand is from China. Total
weight: a relatively hefty 4.87 pounds.
Lehman uses his left hand to press a
button in the crook of the elbow and the
arm begins to move through a repertoire
of automated movements. It bends at the
elbow, then straightens. It bends at the
wrist. Then the hand spins in a complete,
unnerving circle. Finally, the thumb and
forefinger pinch closed, then open again.
It looks like robot tai chi.
Watching the arm intently as it goes
MICHAEL CHOROST ([email protected])
wrote about optogenetics in issue 17.11.
ARM PROSTHESES (1960 S AND 1970 S )
new, and even conventional prosthetics can
take months to master. Lehman thinks practice is helping. “It’s going from where I had
to control the arm and tell it what to do, to
where the arm is actually listening to what I
want it to do,” he says. “The arm is trying to
respond to me.”
Even so, the system is brittle, easily
flummoxed by anything outside the taichi startup sequence. The muscles and
nerves in Lehman’s stump overlap, making the signal noisy, ambiguous. “If you
raise your arm, you can get interference
from other muscles,” says Todd Kuiken,
who invented the reinnervation procedure
at the Rehabilitation Institute’s Center for
Bionic Medicine. “Your deltoid starts to
fire, and the weight of the arm is enough to
change the firing pattern. That could put it
outside the envelope of what works.”
And if Lehman tells the arm to do something it doesn’t understand? To make a
fluid move instead of one built out of its
vocabulary of bends, swivels, and pinches?
“The arm will do something,” says Levi
Hargrove, one of its developers, “but
it won’t do that. It’ll do its best guess.”
This problem bedevils all of the current
research in prosthetics. Today’s computercontrolled prosthetic arms can carry
out only a few commands. “Sometimes
patients come in and they’re expecting a
super-arm that works as good as their old
one,” Kuiken says. “And you have to say no,
I’m sorry, they aren’t that good.”
They were supposed to be better. A
decade ago, researchers seemed on the
cusp of creating a working interface
between body and machine. Even back
then, arms controlled by myoelectric signals were old news; more advanced limbs
would read commands directly from the
brain. In 2003, scientists at Duke
announced that monkeys could control a
robotic arm via electrodes implanted in
their brains. A year later, a similar device
allowed a quadriplegic human patient at
Brown University to play Pong with his
thoughts. In 2008, researchers at the
University of Pittsburgh showed off a monkey that could use a neurally controlled
robotic arm to eat marshmallows. Surely if
a monkey could use a robot arm to feed
itself, it wouldn’t be long before amputees
used them to tie their shoes and pilots flew
jets with their minds.
Such advances are needed more than
ever. There are approximately 185,000 limb
amputations in the US every year—the
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PROSTHETIC ARMS
OLD
VS.
causes range from diabetes to workplace
injuries to battlefield trauma. In 2005, the
most recent year for which data is available, 1.6 million Americans were living
without a limb. As of January 2012 there
were 1,421 amputees from the Afghanistan
war and the second Iraq war. Of those, 254
lost upper limbs, like Lehman, and 420
lost more than one limb. Many of the rest,
presumably, lost single legs or feet, but the
statistics don’t break out those details. In
fact, the numbers seem low—but they’re
the best ones the military will share.
What the military will share, though, is
money to study limb replacements. In 2006,
the Defense Advanced Research Projects
Agency began a program to build, in four
years, an arm “directly controlled by neural
signals” that would have abilities “almost
identical to a natural limb in terms of
motor control and dexterity, sensory feedback (including proprioception), weight,
and environmental resilience.” With its
deadline now three years past, those ambitions now look wildly unrealistic. After
$153 million in funding and years of engineering, the best any amputee can get is a
heavy, clunky arm that moves slowly, can’t
feel anything, and often misreads its user’s
intentions.
“The human arm is amazing,” says Rahul
Sarpeshkar, a bioengineer at MIT who
pioneered the design of ultralow-power
circuitry for bionic interfaces. “It does a
lot of very intelligent local computation
that the brain doesn’t even do. We don’t
understand the coding schemes that biology employs. We don’t understand how
its feedback loops work together.” In other
words, the science hasn’t yet caught up
with the fiction. A true bionic limb—one
that responded to mental commands with
precision and fluidity, one that transmitted sensory information, one that its user
could feel as it moved through space—
would require a depth of understanding
and technological complexity that is simply beyond today’s prosthetic experts. “It’s
not that we’re not going to be able to do it,”
Sarpeshkar says. “But it’s higher-hanging
fruit than people think.” In other words,
this is more than just an engineering problem. It’s a problem of basic science.
NEW
Amputees using these newer,
myoelectric hands consciously contract
a particular muscle in their stump to
activate a particular hand movement.
One of the most useful prosthetic
arms available today, ironically,
uses centuries-old technology.
Here’s how it compares with a truly
bionic limb, which so far exists only
in theory.
2
1
3
CURRENT
1
Extending the arm or flexing the
shoulder pulls a cable attached to
a harness on the user’s back.
2
As the cable tightens, it opens
a split hook at the end of the arm.
Reversing the move closes the
hook.
3
These simple arms are the
lightest limbs on the market, and
they provide a sort of sensory
feedback—force on the prosthetic
hand or arm (like the weight of an
object) gets felt by the user’s body.
THE iLIMB (LEFT, 2008) AND THE
MICHELANGELO HAND (2011)
1
4
3
2
FUTURE
1
Hypothetically, a neurally
controlled prosthesis would begin
with a brain interface, a chip
capable of picking up complex
signals from the user’s brain.
2
A computer would translate
those signals into orders for the
arm—“move up,” “bend my elbow,”
“turn my wrist.”
3
Motors in the joints would move
the arm smoothly in response
to commands from the computer.
4
Sensors in the arm would feed
information on its position and
movement through the computer
and into the chip in the user’s brain.
Across the street from the Rehabilitation
Institute of Chicago, a rhesus monkey
named Thor is strapped into a chair. His
tiny hand clutches a metal handle on the
end of a makeshift arm mounted below
a computer monitor. The arm is hinged;
Thor can’t raise or lower it, but he can
ILLUSTRATION BY JAMES PROVOST
move it side to side and forward and back,
like a salt shaker on a tabletop. And when
Thor moves the handle, a yellow dot on
the screen moves in the corresponding
direction. The monkey gets a sip of juice
when he steers the dot into a box on the
screen. What Thor doesn’t know is that
the handle isn’t wired to anything. It’s just
a mechanical trick to make his brain issue
the right commands. A tiny square array
of 100 electrodes, wired to a computer, is
resting on the part of his brain that controls his arm. The lab around Thor, run by
a neuroscientist named Lee Miller, looks
well used—scuffed floor tiles, jerry-rigged
and discarded machine parts on shelves. A
cat’s brain floats in a jar, unregarded, while
a stack of computers and other electronic
equipment whirs in the corner.
The researchers have spent months analyzing what Thor’s brain does when his
hand moves. They start
by reading his motor output—letting Thor work the
handle when it’s wired to
the cursor and trying to
correlate his movements
to patterns of neural activity. Then they set up the
computer to do the reverse:
to infer his arm motion by
watching neural output.
While Thor works, dozens of pink, yellow, blue,
and green lines writhe on a
monitor, each symbolizing
the intensity and frequency
of individual neural firings.
When a neuron fires, the
computer emits a click.
If you listen, you can tell
how busy Thor’s brain is
under the electrode array.
It sounds like popcorn popping. But then, suddenly,
every line on the monitor
turns gray and freezes. The
clicks stop. A grad student
checks the cables leading to the titanium plug in
Thor’s skull and finds that
one has come loose. He pushes it back into
its socket, and a moment later the monkey
is back in business. The clicking resumes.
It’s a different approach from the one
Kuiken has taken with Lehman. Intuitively,
going straight to the brain seems smarter.
The problem is, no one knows how the brain
does what it does. Neuroscientists know how
neurons work, sending waves of electrical
charge along their lengths and then squirting out chemicals—neurotransmitters—to
signal one another. But how an intention, a
thought, a mind, arises from that network
of electrochemistry-in-aspic is still largely
a mystery. The brain changes from instant
to instant. The same task might be handled
by different neurons at different times.
Moreover, any given set of neurons could
be sending commands to his arm, processing sensory data, or responding to reflexive
movements.
| CONTINUED ON PAGE 130
brain moves the arm when you’re sitting
still, not moving other body parts, not
hearing other things, not being cognitively
loaded,” Shenoy says. It’s a situation that
could exist only in a lab.
Prosthetics
CONTINUED FROM PAGE 105
In 2007, Krishna Shenoy, a neuroscientist
at Stanford, described observing individual
neurons while a monkey did the same task
over and over again. He found that a given
neuron could be very active in one trial and
not at all active on another. Averaged over
many trials, the neuron’s firing was correlated with the monkey’s activity, but on an
event-by-event basis it wasn’t. What is that
neuron really doing? No one has a clue.
So the computer that’s attempting to
translate Thor’s intentions makes a statistical best guess. The array of electrodes in
the monkey’s brain polls about 100 nearby
neurons and selects the closest match it
can find in a database that catalogs what
Thor’s neurons did before. These statistical
inferences are inevitably imprecise; the yellow dot doesn’t move as smoothly as Thor’s
arm. It jitters as if it had stage fright.
Humans don’t do much better. A few
years ago, John Donoghue, a Brown
University neuroscientist, built that Pongplaying brain interface for a quadriplegic
man. Last November, he announced that
he had hooked a paralyzed patient up to a
newer version of his device. On the other
end of it was an advanced arm from DEKA
Research and Development, the company
founded by Segway inventor Dean Kamen.
The patient couldn’t successfully reach out
and grab a ball with the arm more than 50
percent of the time.
When the statistical methods work for
Thor, it’s because his actions are drastically
restricted. The computer was programmed
earlier this week, when Thor was strapped
into the same position he’s in today. He’s
trained to move only one arm in only one
way. This reduces the number of things
his neurons will do, making it more likely
that the computer will recognize a pattern
of neural activity. “We only know how the
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In fact, Thor’s implants would never work in the
real world. The electrodes aren’t attached to
neurons; they’re just sort of floating near
them. So an abrupt head-shake can move
electrodes to different neurons, throwing
off the software’s calibration. “I think it’s a
perfect technology for a spinal-cord patient
who is not very mobile,” says Kuiken. “That
doesn’t translate to an amputee who moves
around and plays football, or falls down and
whacks his head on a door.”
For bigger implants like, say, the deep
brain stimulators used to treat epilepsy and
depression, head movement isn’t a problem. The electrodes in those are huge compared to neurons, and they discharge tiny
electrical shocks into brain tissue rather
than trying to record data from individual
neurons. But for the microscopic needles of
brain-computer interfaces, head motion is
a real problem. They monitor neurons that
are 20 to 50 microns wide. Researchers
have tried to route around this problem by
creating what they call adaptive algorithms
that can adjust when the electrodes shift.
It’s not easy. “If you have an adaptive algorithm and it changes things too quickly, it
confuses the brain,” Miller says. “You’ve
got two systems trying to learn at the same
time, and they essentially learn things out
from under each other.”
Electrodes like Thor’s are vulnerable in a
physical way, too. “The body is a harsh environment,” Donoghue says. “It attacks the
materials and eventually degrades them.”
Electrodes are made of metal. The body is
loaded with water, salt, and a dizzying array
of other chemicals. Putting them together is
like trying to bond a fork and a steak. And
the steak fights back by trying to dissolve
the fork.
The steak treats the fork as a threat—
which, of course, it is. Confronted with
foreign bodies, the brain mounts an inflammatory response called gliosis, wrapping
cells like astrocytes and microglia around
the electrodes to wall them off. Over time,
the electrodes become encapsulated in a
sheath of scar tissue that acts as an insulator. Engineers are working to forestall gliosis with anti-inflammatory coatings and
exotic electrode designs. And in some cases,
gliosis isn’t a problem at all. “We’ve published papers with year-long recordings, and
we have a patient who has nearly five years
of recording,” Donoghue says.
Even so, implants that work well in one
brain may fail in another. “Nobody quite
understands exactly why signals deteriorate, and the rate at which they deteriorate
seems to be wildly unpredictable,” says
Gerald Loeb, a biomedical engineer at the
University of Southern California. “Some
animals will have usable signals for years,
and others lose signals within a couple of
months.” Yet so far, no one has come up
with a better way of getting information
about individual neurons into or out of a
living brain.
Glen Lehman’s arm isn’t clunky because its
motors are slow. By itself, the arm can move
with speed and grace. Robotic arms, after
all, assemble cars and perform surgery. The
hardware isn’t mysterious; thousands of
people use commercial motor-driven myoelectric prostheses, though they’re far from
perfect. (The advances in Lehman’s arm
are largely related to the surgery and the
pattern-recognition software.) The fault in
neural control lies not within the limb but in
the brain—in our incomplete understanding
of not only how to get signals out but how to
send them in.
Animal brains keep track of body parts
with a sort of sixth sense called proprioception. You know exactly where your
right arm is, not because it feels hot or sore
or is touching anything, but because you
just know. Receptors in your limbs send
position-and-motion data through your
nervous system, and it all gets collated,
somehow, into an unconscious awareness.
My arm is up there; my arm is down here.
“There are muscle receptors. There are tendon receptors. There are capsule receptors,
even skin sensors, all contributing in a very
complex way that we don’t understand,”
Kuiken says. “I don’t think there’s going to
be a single spot in the brain where you can
put a dense array of electrodes and get a
strong percept of proprioception.”
Ironically, old-fashioned mechanical arms
first prototyped two centuries ago are better
at giving feedback than anything invented
since. A cable attached to a harness opens
the hook or flexes the elbow when the user
pulls it by reaching forward or shrugging.
Pick something up and force on the prosthesis, translated to your stump, tells you
how heavy it is. Many users actually prefer cable-driven arms to the myoelectric,
motor-driven type.
So what would it take to build an artificial arm that could send proprioceptive
feedback to the brain? In the 1930s the
neurosurgeon Wilder Penfield found that
electrically stimulating the surface of the
brain caused patients to feel sensations and
twitches in specific parts of the body. That’s
where the monkeys come in again. Miller’s
graduate students are working on using the
same kind of electrode array in Thor’s skull
to send electrical signals directly into a part
of the brain that is thought to receive proprioceptive input. (Complicating matters
that the brain is the center of control for the
limbs. But what if it isn’t? It takes 300 milliseconds, almost a third of a second, for the
human arm to send a message to the conscious brain and for the brain to respond. If
that was the only way to control the hand,
we’d never manage to balance trays or
hang up clothes. Those activities require a
degree of fine-motion control that seems to
outpace the speed of signals going to and
from the brain.
That’s what makes some researchers
think that the brain has learned to delegate
fast-response tasks to the spinal cord. It’s
closer to the arm and can respond up to
10 times faster—in just 30 milliseconds.
“The moment-to-moment timing of the
hand’s muscle contractions is dependent
on sensory feedback that is
never going to the brain,” says
Loeb, the USC biomedical
engineer. “It’s being handled
locally.” In other words, the
spinal cord isn’t just a dumb
trunk line. It’s a coprocessor.
Unfortunately, tapping
into the spinal cord is even
tougher than tapping into
the brain. “It’s really hard,”
Donoghue says with a rueful
laugh. “The spinal cord moves
around a lot, so the mechanical problem is
huge. Sticking an electrode in there that
stays in place is a big challenge.”
Loeb has created a rudimentary “virtual
spinal cord,” a software-based substitute
for the fine motor control provided by the
spine. Theoretically, a technology like this
could decode the brain’s high-level intentions and issue supplementary fine motor
commands to a prosthetic limb. Easier said
than done; inferring a brain’s intentions is
the central challenge of brain-machine
interfaces. “If the bionic hand has this sort
of mind of its own,” Loeb says, “what kind
of command signals do we need to get from
the brain to control this semi-autonomous
beast?”
THE BODY IS A
VERY HARSH
ENVIRONMENT.
IT ATTACKS
INVADERS—AND
DEGRADES THEM.
further, this area may also handle tactile
somatosensory feedback—touch.) The idea
is to make a monkey believe that a lever is
jerking in its hand. Eventually, the thinking
goes, they’ll be able to embed sensors in the
arm that transmit the same kind of data.
So far, the test animals do seem to react
as if the handle had moved. After training
them to push the handle to the right when
they feel it move, Miller’s graduate students
send a signal to the electrodes, and the
monkey moves its hand as if it could feel
the handle moving against it. But no one
knows what sensation the input is actually producing. There’s no way to ask the
monkey. Researchers at Caltech and the
University of Pittsburgh, currently working on a neural interface for a fancy, motorized arm created at the Johns Hopkins
University Applied Physics Laboratory,
plan to integrate this kind of sensory data
into human trials in April 2013.
Of course, spending all those resources to
get comprehensible signals into and out of
a brain means buying a central assumption:
Still, researchers in the field remain stubbornly hopeful. At Stanford, Shenoy is now
embedding wireless neural interfaces in
monkeys and then recording their movements with digital cameras. He’s trying to
correlate the neural data with wireframe
graphics of the monkeys in motion. “By
measuring how the brain controls the
arm under more natural, real-world conditions,” Shenoy says, “we’ll at least learn
how the neural activity relates to the arm
in those other situations.” But the data sets
will be enormous. He thinks algorithms for
“dimensionality reduction”—reducing to
just a few critical features what the computer has to interpret—might take care
of the problem. It’s pretty abstract math,
but it’s a way to teach a computer how to
distinguish, let’s say, among hundreds of
breeds of dogs by pulling out just a few
variables, like coat color or ear shape.
The problem is, dimensionality reduction
works best with a ton of raw data—input
from hundreds of thousands of neurons
would be ideal.
It’ll be a long time before anyone can
monitor that many. The number of neurons we can record at one time has doubled
just about every seven and a half years
since 1959. At this rate, it should be possible to monitor 1,000 neurons by 2026.
And researchers will be able to track all 100
billion neurons in a human brain in a mere
220 years.
But what about now? Todd Kuiken ticks
off a list of things that patients can do today
with an arm like Glen Lehman’s: take out
garbage, put on socks, open a jar, pick up
a hat. Optimism seems reasonable in the
long run. Arms and spinal cords and brains
are complex, but they’re not magic.
Last year, Darpa appeared to declare victory over the problem. The agency changed
the language on its website to say that its
researchers had “delivered a prosthetic
arm for clinical trials” that did everything
they promised it would in 2006, including neural control. There is no such arm;
a Darpa public affairs officer says that the
wording of the recent website post was
incorrect, but the agency’s head of prosthetic research wouldn’t answer further
questions.
Back home in Pennsylvania, Glen
Lehman straps on an old-school cable-controlled mechanical arm with a split hook
for gardening or working around the house.
“It can take more abuse,” he says, “and I can
make some of the repairs on my own.” And
every few months Lehman heads back to
the Rehabilitation Institute of Chicago to
practice with his experimental limb and
rewired nerves. This version isn’t anywhere near perfect, but there’s always next
time. And the time after that. !