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BCI Brain

Optogenetics may enter brain therapy mainstream

http://www.npr.org/blogs/health/2013/12/26/256881128/experimental-tool-uses-light-to-tweak-the-living-brain

Optogenetics, the process of controlling brain cells using light, could be used to understand and treat brain diseases, including epilepsy and depression.   Previously, scientists relied on fMRI and a wire probe inserted into the brain to switch on cells.

The technique must be refined before it can be used in people or in remote parts of the brain.

Columbia’s Elizabeth Hillman describes the process:   “Instead of activating just one brain cell at a time with a probe, researchers had a way to cause large groups of cells to fire without touching them. You can select that very specific genetic cell type, and you can tell that specific cell type to react when you shine light on it.  First, though, scientists are going to have to overcome some big challenges.  You’re actually altering the genes of the neurons.”  That’s because most neurons don’t normally respond to light.  Genetic material must be added to every brain cell to control it.  Scientists can do that in mice with genetic engineering, but not in people.  Professor Hillman continues: “Another challenge for optogenetics has to do with delivering light to cells deep in the brain. It’s really hard to get light to go deep,and we all know this just from trying to shine a flashlight through our hand.”

Optogenetics is already changing our understanding of epilepsy.

According to Berkeley professor Hillel Adesnik, “Scientists have known for a long time that epileptic seizures occur when brain cells start firing out of control. But they’ve been struggling to understand the role of brain cells called inhibitory neurons, which can reduce firing in other cells. Prior to optogenetics, there was no way to control these neurons and test hypotheses. Now scientists have shown that by altering that activity of inhibitory neurons in mice, it’s possible to start and stop epileptic seizures.”

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BCI Brain Sensors

Microscale torsional muscle system can simulate active neuromuscular system

http://newscenter.lbl.gov/news-releases/2013/12/19/a-micro-muscular-break-through/

U.S. Department of Energy and Lawrence Berkeley National Laboratory researchers have developed a micro-sized robotic torsional muscle/motor made from vanadium dioxide. For its size, it is a thousand times more powerful than a human muscle, able to catapult objects 50 times heavier than itself over a distance five times its length within 60 milliseconds.

“Multiple micro-muscles can be assembled into a micro-robotic system that simulates an active neuromuscular system,” said Berkely professor Junqiao Wu.  “The naturally combined functions of proximity sensing and torsional motion allow the device to remotely detect a target and respond by reconfiguring itself to a different shape. This simulates living bodies where neurons sense and deliver stimuli to the muscles and the muscles provide motion.”

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AI BCI Brain Crowdfunding

Crowdfunded 3-D augmented reality glasses aim to compete with Google Glass

https://www.spaceglasses.com/

For several months, after a successful Kickstarter campaign, Meta has been developing augmented reality glasses “that combine the power of a laptop and smartphone in a pair of thick Ray-Bans and a small pocket computer.”

The Meta Pro will have an i5 CPU, 4GB of RAM, 128 GB of storage, Wi-Fi 802.11n and Bluetooth 4.0 connectivity. It will cost $3,000, and the company hopes to ship by June.

Meta is hoping to compete with Google Glass, although it is not currently wireless.  The glasses have 15x the display of Google Glass, and runs 3-D instead of 2-D. Its optics are thinner, at 2mm vs 5mm, and its sensors recognize hand gestures, which makes control easier than touching the side of your face.

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BCI Brain

EEG patch monitors attention in students

 http://www.calcalist.co.il/local/articles/0,7340,L-3619747,00.html

http://www.calcalist.co.il/local/articles/0,7340,L-3620186,00.html

Professor Nathan Intrator of Tel Aviv University’s Blavatnik School of Computer Science and Sagol School of Neuroscience, and Guy Levi, Chief Innovation Officer of Israel’s Center for Educational Technology are disrupting education through brain science.

In an attempt to improve learning abilities in children with attention issues, Intrator and Levi attach a patch to student’s foreheads to measure brain activity during lessons.  The learning process can then be adapted to their skills and needs. A student’s lack of attention is identified and better methods or times for delivery of information are suggested.

Through advanced signal processing, Intrator uses a patch with three electrodes to extract information about attention and cognitive strategies.

This less obtrusive approach allows widespread use of EEG in diagnostic studies. Intrator’s current focus includes attention, dementia, and sleep.

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AI BCI Brain

Year end review of “neuromorphic” chip prototypes

http://www.technologyreview.com/featuredstory/522476/thinking-in-silicon/

MIT Technology Review today features an overview of processors that they claim are “about to narrow the gulf between artificial and natural computation—between circuits that crunch through logical operations at blistering speed and a mechanism honed by evolution to process and act on sensory input from the real world.”

Caltech’s Carver Mead pioneered “brain inspired” computing in the 1980’s, based on theoretical math and logic.  ApplySci has featured related research from The University of Zurich/ETH, DARPA, Intel, IBM, Qualcomm, and others, as well as the “deep learning” initiatives of Google and Facebook.  We anticipate and will report on advances in this space in the coming year.

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AI Assistive Technologies BCI Brain

Nerve interface simulates touch in prosthetic hand

http://www.technologyreview.com/news/522086/an-artificial-hand-with-real-feelings/

Cleveland Veterans Affairs Medical Center and Case Western Reserve University researchers have developed an interface that can convey a sense of touch from 20 spots on a prosthetic hand. It directly stimulates nerve bundles, known as peripheral nerves, in the arms of patients.   Two people have been fitted with the interface to date. The implants continue to work after 18 months, which is notable because electrical interfaces to nerve tissue can gradually degrade in performance.

According to Case Western Professor Dustin Miller, who is leadning the project:  “The work opens up the possibility that prosthetic limbs could one day provide enduring and nuanced feedback to humans.”

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Assistive Technologies BCI Brain Sensors

Nerve impulse sensor exoskeleton assists paraplegics, Parkinson’s, stroke patients

http://www.dw.de/standing-again-with-nerve-controlled-robotics/a-17280419

Professor Thomas Schildhauer leads a team at Bergmannsheil University Clinic’s “Center for Neuro-Robotic Mobility Training”  that uses nerve impulse sensors to help patients walk again.  A robotic exoskeleton with sensors affixed to the hips and legs gives paraplegics, Parkinson’s and stroke patients a sense of stability during ambulatory exercises. The robot suit contains numerous sensors that recognize nerve impulses as they flash across the skin. Via a small motor, the suit converts those impulses into motion.

“The brain sends a signal out that typically arrives at the muscle via nerve systems,” said Schildhauer.  For patients capable of some movement, “Small impulses can still be discovered in the muscles. And they can be measured and recorded on the skin. That signal is then amplified in the robot and moves the motors of the exoskeleton.”

Such robot-supported training, Schildhauer says, “seems to build up and expand the remaining muscle functions, and the brain structures, too, that haven’t been used for a long time.” Movement patterns, he added, are then re-trained. “It seems to cause the patient to fall back into many of the old, usual cycles of movement, and results in them being able to walk again.”

Categories
BCI Brain Stroke

Thought controlled device helps stroke patients move limbs

https://www.radiology.wisc.edu/research/currentProjects_details.php?id=368

http://www.sacbee.com/2013/12/01/5961969/novel-rehabilitation-device-improves.html

Professor Vivek Prabhakaran at the University of Wisconsin is developing a device that combines a brain-computer interface with electrical stimulation of damaged muscles to help stroke patients relearn how to move limbs.  Eight patients who had lost movement in one hand have been through six weeks of therapy with the device. They reported improvements in their ability to complete daily tasks.

Patients wear a cap of electrodes that picks up brain signals. Those signals are decoded by a computer. The computer sends tiny jolts of electricity through wires to sticky pads placed on the muscles of a patient’s paralyzed arm. The jolts act like nerve impulses, telling the muscles to move.  A video game prompts patients to try to hit a target by moving a ball with their affected arm. Patients practice with the game for two hours, every other day.

Researchers scanned the patients’ brains before, during and a month after they finished 15 sessions with the device.  The more patients practiced, the more they were able to train their brains.

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BCI Brain

Emotion detection via expression reading algorithms

http://www.nytimes.com/2013/12/01/technology/when-algorithms-grow-accustomed-to-your-face.html

The emotion reading market, based on facial recognition aglorithms, is developing rapidly.

Companies in this field include Affectiva and Emotient. Affectiva used webcams over two and a half years to accumulate and classify about 1.5 billion emotional reactions from people as they watched streaming video.  These recordings served as a database to create the company’s face-reading software, which it will offer to mobile software developers starting in mid-January.

Categories
Assistive Technologies BCI Sensors Wearables

Tongue based magnetic field controls wheelchair

http://stm.sciencemag.org/content/5/213/213ra166

Maysam Ghovanloo of Georgia Tech and Anne Laumann of Northwestern have developed a tongue piercing based magnet to operate a wheelchair.

The device is a small magnetic barbell which creates a magnetic field in the mouth. When users flick their tongues, it alters that field. The change is picked up by four small sensors on a headset with twin extensions curving around the cheeks, and relayed wirelessly to a smartphone, computer or iPod. The software translates the signals and sends them to a powered wheelchair or computer.

The system was tested on 11 tetraplegia patients from rehabilitation centers in Chicago and Atlanta and 23 able volunteers who already wore tongue jewelry.

After 30 minutes of training, everyone was able to move a computer cursor, clicking on targets on a laptop screen, playing video games and dialing phone numbers. Accuracy and speed improved with practice, even though subjects used the system only one day a week. After six weeks the tetraplegics were, on average, three times faster with the tongue system than with sip-and-puff, which six of the 11 had been using. It was equally accurate.

Using only tongue movements, the volunteers also navigated a powered wheelchair through a 50-meter-long course with 13 turns, 24 obstacles and occasional alarms signaling “Stop! Emergency!” Here, too, on average the 11 tetraplegics drove the course three times faster with the tongue system than with sip-and-puff, and just as accurately.

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Assistive Technologies BCI Brain

Monkeys in Nicolelis lab control both arms using brain activity

http://stm.sciencemag.org/content/5/210/210ra154.short?rss=1

Duke’s Miguel Nicolelis continues to advance brain machine interface, and in his latest experiment, monkeys have learned to control the movement of both arms on an avatar using their brain activity.

The findings  advance efforts to develop bilateral movement in brain-controlled prosthetic devices for severely paralyzed patients.  Until now brain-machine interfaces could
only control a single prosthetic limb.

Categories
Assistive Technologies BCI

“Bionic” arm exoskeleton concept for rehabilitation and strength augmentation

http://titanarm.com/about

Titan Arm is an untethered, powered, upper body exoskeleton concept for use in rehabilitation and therapeutic applications, which can also augment strength.  It is under development and not yet ready to be brought to market, but is being designed by students at The University of Pennsylvania.  It straps directly to a user’s right arm to help lift heavy objects. Its inventors believe that it will be useful in aiding physical rehabilitation, both for people who have suffered upper body injuries and for those with pre-existing muscular-skeletal disorders.  The bionic limb can lift approximately 40 pounds of weight, and is predominantly made of aluminum and steel components, and powered by a DC battery.