Archive for the ‘Defense Advanced Research Projects Agency’ Category

DARPA, the Defense Advanced Research Projects Agency, has developed new paddles that allow users to climb vertical walls like Spider-man. For the first time in history, a fully-grown person climbed a glass wall more than two stories in the air.

The Z-man program aimed at designing a new tool for soldiers to use when climbing walls. Traditionally, fighters in wartime have had to rely on ladders and ropes to overcome vertical surfaces. These are both noisy and bulky, making it difficult for warriors to climb quietly when needed.

“The gecko is one of the champion climbers in the Animal Kingdom, so it was natural for DARPA to look to it for inspiration in overcoming some of the maneuver challenges that U.S. forces face in urban environments,” Goodman said.

This challenge was one many species had already faced in the wild. Geckos, able to climb vertical surfaces, were an inspiration to the inventors.

“[N]ature had long since evolved the means to efficiently achieve it. The challenge to our performer team was to understand the biology and physics in play when geckos climb and then reverse-engineer those dynamics into an artificial system for use by humans,” Matt Goodman, DARPA program manager for the Z-Man program, told the press.

The lizard uses microscopic tendrils, called setae, that end with flat spatulae. This dual structure provides the creature with an extremely large surface area coming into contact with whatever it touches. This allows van der Waals forces, a magnetic attraction between atoms, to hold the lizard in place. This same technique is used for the paddles.

Draper Laboratory, headquartered in Cambridge, Massachusetts assisted the military technology developers in creating the devices. The business developed the unique microstructure material needed to make the design work.

The demonstration climb involved a climber weighing 218 pounds, in addition to a 50-pound load in one trial. He ascended and descended the vertical glass surface, using nothing but a pair of the paddles.

Warfare constantly advances in technology and strategies, but ropes and ladders – still needed to scale walls – have not significantly changed in thousands of years.

“‘Geckskin’ is one output of the Z-Man program. It is a synthetically-fabricated reversible adhesive inspired by the gecko’s ability to climb surfaces of various materials and roughness, including smooth surfaces like glass,” DARPA officials wrote on the Z-man Web site.

Advances in this bio-inpspired technology could have benefits beyond the battlefield. Materials similar to the the structure in the pad could be used as temporary adhesives for bandages, industrial and commercial products.

http://www.techtimes.com/articles/8287/20140610/gecko-inspired-darpa-paddles-become-spider-man.htm

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In a proposal almost as fanciful as the fictional 20,000 Leagues Under the Sea by Jules Verne, the Defense Advanced Research Projects Agency kicked off a research project last Friday to develop sensor systems that could be placed miles below the surface of the ocean and activated when needed by a remote command.

DARPA said it wants to develop a system that can store unmanned sensors such as waterborne or airborne cameras, decoys, network nodes, beacons and jammers, in watertight capsules that can withstand pressure at depths up to six kilometers (3.7 miles) and then be launched to the surface “after years of dormancy.”

Nearly half of the world’s oceans have depths deeper than 4 kilometers (2.5 miles), DARPA said, “which provides a “vast area for concealment of storage” and this concealment “also provides opportunity to surprise maritime targets from below, while its vastness provides opportunity to simultaneously operate across great distance,” DARPA said.

The agency said it envisions the subsystems of its Upward Falling Payloads projects will consist of a sensor payload, a “riser” providing pressure tolerant encapsulation of the payload and a communication system triggering launch of the payload stored on a container with an inner, 4-7/8 inch diameter and a length of 36 inches.

In the first stage of the three-phase project expected to cost no more than $1.75 million, DARPA wants researchers to concentrate on a communications system that avoids “false triggers” of the deep-sea systems and can operate at long distances from the submerged sensors. Proposals for this phase also should detail the design of a capsule and riser system that will work after sitting for years on the seabed, and potential sensor systems for military or humanitarian use.

The second phase of the project calls for the communication system to “wake up” the system on the seabed and launch it, with tests planned the Western Pacific in 2015 and 2016,though tests also could be conducted in the Atlantic or offshore from Hawaii, DARPA said.

In the third phase, planned for 2017, DARPA plans tests of a completely integrated and distributed Upward Falling Payloads system at full depth in the Western Pacific.

Proposals are due March 12 and DARPA expects to make an award in June.

http://www.nextgov.com/defense/2013/01/darpa-eyes-pop-deep-sea-sensors/60655/

Thanks to Kebmodee for bringing this to the attention of the It’s Interesting community.

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Scientists are reporting an advance toward development of a pill that could become celiac disease’s counterpart to the lactase pills that people with lactose intolerance can take to eat dairy products without risking digestive upsets.

They describe the approach, which involves an enzyme that breaks down the gluten that causes celiac symptoms, in the Journal of the American Chemical Society.

Justin Siegel, Ingrid Swanson Pultz and colleagues explain that celiac disease is an autoimmune disorder in which the gluten in wheat, rye or barley products causes inflammation in the digestive tract. Enzymes in the stomach break down gluten into smaller pieces, called peptides. For most people, these peptides are harmless. But for the 2 million-3 million Americans with celiac disease, the peptides trigger an autoimmune response and painful symptoms. Currently, the only treatment is a gluten-free diet. However, the scientists reasoned that if an enzyme could further break down the offending peptides in the stomach, celiac patients might be able to eat gluten-containing foods.

They describe discovery of a naturally occurring enzyme that has some of the ideal properties for doing so. The scientists modified the enzyme in the laboratory so that it would meet all the necessary criteria. The new enzyme (called KumaMax) broke down more than 95 percent of a gluten peptide implicated in celiac disease in acidic conditions like those in the stomach. “These combined properties make the engineered [enzyme] a promising candidate as an oral therapeutic for celiac disease,” say the researchers.

The authors acknowledge funding from the Howard Hughes Medical Institute and the Defense Advanced Research Projects Agency.

Journal Reference:

1.Sydney R. Gordon, Elizabeth J. Stanley, Sarah Wolf, Angus Toland, Sean J. Wu, Daniel Hadidi, Jeremy H. Mills, David Baker, Ingrid Swanson Pultz, Justin B. Siegel. Computational Design of an α-Gliadin Peptidase. Journal of the American Chemical Society, 2012; 134 (50): 20513 DOI: 10.1021/ja3094795

http://www.sciencedaily.com/releases/2012/12/121219133558.htm

 

 

Stanford researchers have designed the fastest, most accurate mathematical algorithm yet for brain-implantable prosthetic systems that can help disabled people maneuver computer cursors with their thoughts. The algorithm’s speed, accuracy and natural movement approach those of a real arm.

 

 

On each side of the screen, a monkey moves a cursor with its thoughts, using the cursor to make contact with the colored ball. On the left, the monkey’s thoughts are decoded with the use of a mathematical algorithm known as Velocity. On the right, the monkey’s thoughts are decoded with a new algorithm known as ReFITT, with better results. The ReFIT system helps the monkey to click on 21 targets in 21 seconds, as opposed to just 10 clicks with the older system.

 

 

When a paralyzed person imagines moving a limb, cells in the part of the brain that controls movement activate, as if trying to make the immobile limb work again.

Despite a neurological injury or disease that has severed the pathway between brain and muscle, the region where the signals originate remains intact and functional.

In recent years, neuroscientists and neuroengineers working in prosthetics have begun to develop brain-implantable sensors that can measure signals from individual neurons.

After those signals have been decoded through a mathematical algorithm, they can be used to control the movement of a cursor on a computer screen – in essence, the cursor is controlled by thoughts.

The work is part of a field known as neural prosthetics.

A team of Stanford researchers have now developed a new algorithm, known as ReFIT, that vastly improves the speed and accuracy of neural prosthetics that control computer cursors. The results were published Nov. 18 in the journal Nature Neuroscience in a paper by Krishna Shenoy, a professor of electrical engineering, bioengineering and neurobiology at Stanford, and a team led by research associate Dr. Vikash Gilja and bioengineering doctoral candidate Paul Nuyujukian.

In side-by-side demonstrations with rhesus monkeys, cursors controlled by the new algorithm doubled the performance of existing systems and approached performance of the monkey’s actual arm in controlling the cursor. Better yet, more than four years after implantation, the new system is still going strong, while previous systems have seen a steady decline in performance over time.

“These findings could lead to greatly improved prosthetic system performance and robustness in paralyzed people, which we are actively pursuing as part of the FDA Phase-I BrainGate2 clinical trial here at Stanford,” said Shenoy.

The system relies on a sensor implanted into the brain, which records “action potentials” in neural activity from an array of electrode sensors and sends data to a computer. The frequency with which action potentials are generated provides the computer important information about the direction and speed of the user’s intended movement.

The ReFIT algorithm that decodes these signals represents a departure from earlier models. In most neural prosthetics research, scientists have recorded brain activity while the subject moves or imagines moving an arm, analyzing the data after the fact. “Quite a bit of the work in neural prosthetics has focused on this sort of offline reconstruction,” said Gilja, the first author of the paper.

The Stanford team wanted to understand how the system worked “online,” under closed-loop control conditions in which the computer analyzes and implements visual feedback gathered in real time as the monkey neurally controls the cursor toward an onscreen target.

The system is able to make adjustments on the fly when guiding the cursor to a target, just as a hand and eye would work in tandem to move a mouse-cursor onto an icon on a computer desktop.

If the cursor were straying too far to the left, for instance, the user likely adjusts the imagined movements to redirect the cursor to the right. The team designed the system to learn from the user’s corrective movements, allowing the cursor to move more precisely than it could in earlier prosthetics.

To test the new system, the team gave monkeys the task of mentally directing a cursor to a target – an onscreen dot – and holding the cursor there for half a second. ReFIT performed vastly better than previous technology in terms of both speed and accuracy.

The path of the cursor from the starting point to the target was straighter and it reached the target twice as quickly as earlier systems, achieving 75 to 85 percent of the speed of the monkey’s arm.

“This paper reports very exciting innovations in closed-loop decoding for brain-machine interfaces. These innovations should lead to a significant boost in the control of neuroprosthetic devices and increase the clinical viability of this technology,” said Jose Carmena, an associate professor of electrical engineering and neuroscience at the University of California-Berkeley.

Critical to ReFIT’s time-to-target improvement was its superior ability to stop the cursor. While the old model’s cursor reached the target almost as fast as ReFIT, it often overshot the destination, requiring additional time and multiple passes to hold the target.

The key to this efficiency was in the step-by-step calculation that transforms electrical signals from the brain into movements of the cursor onscreen. The team had a unique way of “training” the algorithm about movement. When the monkey used his arm to move the cursor, the computer used signals from the implant to match the arm movements with neural activity.

Next, the monkey simply thought about moving the cursor, and the computer translated that neural activity into onscreen movement of the cursor. The team then used the monkey’s brain activity to refine their algorithm, increasing its accuracy.

The team introduced a second innovation in the way ReFIT encodes information about the position and velocity of the cursor. Gilja said that previous algorithms could interpret neural signals about either the cursor’s position or its velocity, but not both at once. ReFIT can do both, resulting in faster, cleaner movements of the cursor.

Early research in neural prosthetics had the goal of understanding the brain and its systems more thoroughly, Gilja said, but he and his team wanted to build on this approach by taking a more pragmatic engineering perspective. “The core engineering goal is to achieve highest possible performance and robustness for a potential clinical device,” he said.

To create such a responsive system, the team decided to abandon one of the traditional methods in neural prosthetics.

Much of the existing research in this field has focused on differentiating among individual neurons in the brain. Importantly, such a detailed approach has allowed neuroscientists to create a detailed understanding of the individual neurons that control arm movement.

But the individual neuron approach has its drawbacks, Gilja said. “From an engineering perspective, the process of isolating single neurons is difficult, due to minute physical movements between the electrode and nearby neurons, making it error prone,” he said. ReFIT focuses on small groups of neurons instead of single neurons.

By abandoning the single-neuron approach, the team also reaped a surprising benefit: performance longevity. Neural implant systems that are fine-tuned to specific neurons degrade over time. It is a common belief in the field that after six months to a year they can no longer accurately interpret the brain’s intended movement. Gilja said the Stanford system is working very well more than four years later.

“Despite great progress in brain-computer interfaces to control the movement of devices such as prosthetic limbs, we’ve been left so far with halting, jerky, Etch-a-Sketch-like movements. Dr. Shenoy’s study is a big step toward clinically useful brain-machine technology that has faster, smoother, more natural movements,” said James Gnadt, a program director in Systems and Cognitive Neuroscience at the National Institute of Neurological Disorders and Stroke, part of the National Institutes of Health.

For the time being, the team has been focused on improving cursor movement rather than the creation of robotic limbs, but that is not out of the question, Gilja said. Near term, precise, accurate control of a cursor is a simplified task with enormous value for people with paralysis.

“We think we have a good chance of giving them something very useful,” he said. The team is now translating these innovations to people with paralysis as part of a clinical trial.

This research was funded by the Christopher and Dana Reeve Paralysis Foundation, the National Science Foundation, National Defense Science and Engineering Graduate Fellowships, Stanford Graduate Fellowships, Defense Advanced Research Projects Agency (“Revolutionizing Prosthetics” and “REPAIR”) and the National Institutes of Health (NINDS-CRCNS and Director’s Pioneer Award).

Other contributing researchers include Cynthia Chestek, John Cunningham, Byron Yu, Joline Fan, Mark Churchland, Matthew Kaufman, Jonathan Kao and Stephen Ryu.

http://news.stanford.edu/news/2012/november/thought-control-cursor-111812.html

Thanks to Kebmodee for bringing this to the attention of the It’s Interesting community