How can biometric technology possibly help shepherds keep their sheep safe? Well, an experiment in Europe may shed some light on just how effective this kind of tactic could be. Not only could this solution be effective, but it could even save shepherds thousands of dollars. Apparently, good sheepdogs are more expensive to keep than smartphones.

The device is a high-tech collar attached to the sheep themselves. The collar has a heart rate monitor similar to those athletes use. In an experiment using twelve sheep and two muzzled Czechoslovakian wolfdogs, the sheeps’ heart rates made an impressive jump: from 80 to 225 beats per minute.

These results prompted to designers to build a version of the device that not only sends this warning information straight to the shepherd’s smartphone but also emits a repellent to drive away the attacker. This new collar is expected to be test-worthy by the end of this year, and a prototype will be officially released for broader testing in 2013.

This offers a whole new realm to shepherds and ranchers worldwide. While effective, sheepdogs are expensive to house, feed, and replace. These collars could not only save thousands of dollars in the cost of sheepdogs, but thousands more in the cost of losing livestock.

It also opens up newer realms for biometric technologies. From the lab to the field–in a more literal sense.

A study by researchers Moreno Coco and Frank Keller at the University of Edinburgh, UK, demonstrated that visual attention is extremely closely related to what people say when describing a scene.

Coco and Keller showed twenty-four participants a series of indoor scenes while tracking their eye movements. They participants were asked to describe each scene after seeing it. They weren’t structured in how they had to describe–they were allowed to freely discuss the images in their own structure. The researchers found a surprising tendency for the participants to describe the scene in the same order they looked at different objects.

For example, in a hotel scene, if they said, “The man was standing at the desk in the hotel lobby, and his suitcase is on the floor,” they likely noticed first the man, then the desk, then the lobby, then the suitcase on the floor.

Due to the complex cognitive process used to actually create sentences, the researchers were surprised at the close correlation between speech and visual attention.

Following this experiment, Coco and Keller are now trying to determine if they can predict which actual sentences people will use to describe a scene solely based on their eye movements. They created an algorithm that used the gaze tracking data accumulated from the aforementioned experiment to accurately predict correct statements out of 576 options. That’s pretty impressive.

Peter Kirn, a musician from Kentucky, is using electrically charged pennies to record the electrical currents in his body (galvanic skin response) to create synthesized music. Based on his mood, the music changes. And Kirn is only one of many artists experimenting with biometric music techniques.

Another artist, Marco Donnarumma from Italy, uses his muscles to create music. The sound comes literally from the muscle itself: the friction of tissues moving. He uses a microphone that takes the low frequency sound and makes them audible. He literally “plays his body” by simply moving to create rhythms.

Claudia Robles Angel is another musician who uses biometrics. Her particular approach is through EEG, where she forces herself into a state of calm or one of stress through meditation and breathing to crate her own music.

This is called “musical biofeedback,” and many artists are starting to toy with the idea. The above three musicians were among several others who showcase their work in Berlin. The field is growing.

The artists agree that using their own biometric measurements to create music has put them more in-tune with their bodies. Donnarumma uses his entire muscular system to create his music, while Kirn and Robles Angel have really mastered the way they think.

It’s an interesting approach, and it will be more interesting to see how this field changes as biometric science improves.

A recent study by this group published in Cognitive Processing discovered that twenty top-tier managers scored higher on the Brain Integration Scale, Gibbs’s Socio-moral Reasoning questionnaire, and an inventory of peak experiences than did twenty low-level managers. This is the fourth study of its kind, previous ones comparing the brain function of extremely talented athletes and performers to the average. The results were the same.

The studies were conducted using EEG to test three primary areas: coherence, alpha waves, and how economically the brain functioned. Basically, they were trying to determine how well the brain worked together in an integrated way.

People with extremely high performance levels in all three arenas (musical, athletic, and managerial) showed much more developed brain integration. This observation has developed a new theory: that more advanced brain-mind development creates a platform that makes higher performance possible in any arena.

It’s an interesting concept, but there are things that haven’t been answered yet. For one, can you develop your brain further to achieve these goals, or are you trapped in a box dependent on your mind-brain development? Also, can you measure a child or young person’s brain to determine if they have that potential early on?

Only time will tell, but in the meantime, what an interesting concept!

The company behind the technology is a Massachusetts-based startup called Affectiva. The devices have already been used in market research to determine consumer’s emotional response to various forms of advertising: education is the new frontier.

But many teachers are skeptical. People think it’s an invasive and “creepy” technology and, since GSR can’t tell the difference between fear, excitement, and sexual arousal, there’s absolutely no way it can properly identify when students are truly engaged with what is actually going on in the classroom or if they’re just distracted by the cute girl in front of them.

Still, the project could end up a success, and we’ll know soon. The Gates foundation has given $1.4 million dollars in grants to university researchers, who will begin testing in middle schools this fall.

What do you think? Is using biometric data intrusive and unnecessary or a revolutionary new field for education?

When you think about “eye tracking” and “camera” in the same sentence, the camera is often the element implementing the actual eye tracking. Infrared cameras are popularly used to actually capture images of the eyes in order to enable eye tracking to actually take place. Today, however, the eyes are implementing the camera.

Mimi Zou is an innovation design engineer from the Royal College of Art in London. She is working on a prototype camera controlled by eye tracking. The project, called Iris, is an attempt to make a camera that adapts to you just as much as you adapt to it.

Eye tracking controls all the major mechanics of the prototype camera. Squinting makes it zoom in, opening your eyes makes it zoom out, and blinking twice makes activates the shutter. Additionally, one proposed feature to the Iris system is biometric recognition. Basically, the camera can recognize you by your eyes and set your preferred defaults automatically.

Talk about intuitive!

It may be a while yet until we can see the Iris system on the market. There are still major hurdles to overcome to bringing this prototype to a real product. However, Zou is optimistic, and so are we.

As it stands, there is already a 56% misunderstanding rate for these warning labels, according to the United States Pharmacopeial Convention. This research set out to discover why.

The study used eye tracking technology to determine whether or not these labels were noticed. Results showed that fewer than 50% of participants actually read the warning labels. Additionally, 22% didn’t notice the labels at all. The researchers speculate that, though the warning label had a brighter color, the smaller text and awkward text alignment (vertical up the side of the bottle instead of horizontal with the text of the main label) played a part in making the warning label seem less important than the primary one.

The groups were also differentiated by age. Participants ranged from 20 to 77, and, while almost everyone paid attention to the main label, only 29% of participants aged 51 to 77 noticed the warning. Considering that one third of people over the age of sixty-five take an estimated ten medications per day, this result can be troubling.

Misunderstanding or completely missing this warning information can mean the difference between life and death. Many side effects are directly related to not heeding these warnings, and some of those side effects can have dramatic results.

However, this initial study was small. It consisted of fewer than forty participants, and the tracker determined color recollection rather than the actual content of the warning label. Nonetheless, the study both demonstrates the usefulness of eye tracking in further studies as well as the potential risks of poor warning labels.

Prototype systems bragging costs lower than $3,000 dollars are becoming more and more abundant, but people in the more expensive eye tracker business have to wonder what is traded to make the lower cost even possible. You’ll read stories of heroics, of a very small team that was able to create a phenomenal product with one tenth of the manpower bigger companies employ (costs of hiring and paying are assumed to stretch into end-sales prices) or monopolized companies boosting price thanks to low competition, but what it really comes down to is the quality of materials used to make the systems.

Many high-priced companies have technologies built into their machines that cost more than the low-cost systems do fully assembled. Single components can be so complex and high-tech that they alone carry more than the price of these other systems. Many of these components may also be specially built or designed for the product itself.

Additionally, many of these systems have complex software that does much more than simply track the eyes. Systems with bigger software bundles and more features realistically will cost more to assemble than systems with a single purpose.

That said, many of the cheap systems can’t compete with the quality more expensive systems can boast. The technology simply can’t compete, which makes it hard to justify for research fields that need absolute precision. However, for markets such as assistive tech where accuracy is not as vital, these systems could provide a cost-efficient alternative.

There are seven kinds of biometric systems that are really popular in this arena.

Fingerprint Identification
This is one of the earliest biometric identification systems around. Fingerprints are valuable to this market because they do not change over time and are completely unique to the individual person.

Face Recognition
This is a natural biometric identification that humans use in-person, and is somewhat difficult to automate. Facial recognition typically measures the distance between facial landmarks. Unlike fingerprints, facial construction changes drastically over time.

Hand Geometry
This method is commonly used in juncture with other biometric identification systems as a back-up support. Hand geometry is less unique than other biometric systems, so it is not as reliable when used on its own.

Voice Analysis
Many consumers prefer using voice analysis compared to other biometrics. Voices can change over time, and sickness and other physical conditions that affect the voice can make verification difficult.

Iris Scanning
Like fingerprints, irises are completely unique to the individual person, which makes the method more foolproof than others. An iris scan can be somewhat intrusive, though, and the technology is more expensive than other methods.

Retina Scanning
Retina scans look at the blood vessels at the back of the eye, which is another biometric feature that is completely unique and doesn’t change throughout a person’s lifetime. Like iris scanning, it can be intrusive and expensive.

Handwriting Analysis
Throughout history, handwriting has been used as a form of identification. There are some slight inconsistencies to a person’s signature, but overall combining pen speed, timing, and pressure alongside the actual handwriting itself makes it a valid measurement.

Though Shimmer Research is still in the early stages of Sensum, they eventually hope to create a device and application that can work in unison with actual television, movie, or video game content to change the story dependent on the user’s experience. If the user is highly involved emotionally, based on their GSR and heart rate, the movie will respond with even more intense content. This could include music changes, scene changes, and alternate endings.

This opportunity may not be too far in the future. Prototypes have already been tested, and the Sensum team is working with Ian McDonald, a science fiction screenplay writer, to create a movie specifically for application.

The Sensum application opens up a whole new world of consumer interaction. Imagine the value individual viewers can get from movies and video games tailored to their own emotional reaction. It could be the next thing in true immersion, giving each individual person a unique experience.