(Screenshot by Michelle Starr/CNET Australia)
A wearable eyepiece measures physiological responses such as pupil dilation and perspiration to find content on the web that will interest you.
What if Google Glass could tell when you were interested in something — and recommend personally curated content based on a cumulative database of your likes and dislikes?
We've already seen tech that responds automatically to your physiological responses; blinking to, for example, to scroll a web page, even gaming peripherals, such as an and a .
None of these, however, have really made their way into the mainstream — but the technology has definite potential. Take a concept created by Sanya Rai, Carine Collé and Florian Puech, students at the Royal College of Art and Imperial College in the UK.
It's called Amoeba, and it's an eyeglass designed to be worn when you spend time on the web.
"We envision that you would wear the Amoeba device before you start your web-based research," Rai wrote on her website. "As you go through different web pages, the device senses your bio-data and quantifies your interest. When you are done, you can then go to the Amoeba app and select the keyword you were looking at. The app will show you a time-based summary of all links visited, layering them based on how interesting you found the content. You also have the option of seeing the route you took to arrive at a certain page, thus enabling better reflection and self awareness."
The device has sensors to measure three involuntary physical responses: your perspiration rate, your pupillary dilation and your respiration rate. A branch at the top touching the side of the wearer's head measures the skin's electrical conductance — which varies according to perspiration — a camera in the eyepiece measures pupillary dilation, and a heat sensor near the nose and mouth measures respiration.
The system was tested on several subjects, who were invited to read four articles for one minute each. Using the feedback provided by the prototype system, the team could accurately pinpoint which articles the subject had liked most and least in nine out of ten people.
The team believes this could have several potential uses. Firstly, providing advertisers with honest feedback. Another is measuring student engagement in education. For the user, of course, it could help unearth content that they otherwise might not find for themselves — a pretty intriguing prospect, although we suspect some might baulk at the notion that everything they engage with is being fed to a database and potentially sold.
Still, at the moment it's only a concept, and one would hope it would remain optional, even if the team were to achieve their dream. "Our final vision would be to have Amoeba as an embedded feature in all wearable devices so that it can help streamline all content for the user, bringing to the forefront only the most interesting stuff rather than the entire daily log of data," Rai said.