Brain Imaging Technologies Will Filter Information Based On The User’s Brain Activity
Every day you are faced with streams of information like EMAILS, tweets, Facebook posts, texts, etc … endless sources of distraction. And what if your computer knew what you wanted and you could stay focused on the task at hand? Information overload in stressful jobs would be less with a smart device that could read user’s mind to gauge the concentration level and sensibly filter information for the user based on the activity in their brain. Evan M. Peck, a PhD candidate studying in the Human-Computer Interaction lab at Tufts University in Medford, Massachusetts is conducting a research on using the brain as passive input to adaptive interfaces using functional near-infrared spectroscopy (fNIRS). Peck in collaboration with Remco Chang, an assistant professor of computer science in the Tufts School of Engineering focus on designing a system that would enable computers to directly monitor your brain as you work, responding to your needs in real time. The system uses a headset that beams infrared light from emitters on a user’s forehead into their prefrontal cortex, a part of the brain associated with planning and decision-making. By measuring the amount of light reaching receivers on the forehead, the system can determine when a user is concentrated or not; then matching the readings to what a user is looking at on a screen allows the system to decide what information is useful. Peck is currently working on an fNIRS recommendation system that would take active user rating out of the equation, and would simply “read” brain activity as an indicator of preference of just about anything: movies, cars or music. The next step is to build a brain interface that can handle more complex interactions, like filtering emails and the other information a modern worker faces daily. Peck envisions that computers will soon learn to predict, what emails are important and what are not, then the system could determine when someone is busy and only interrupt them if an incoming piece of information is deemed important. The research may radically change the way our society works.
Via:newscientist.com, eecs.tufts.edu
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