Tufts researchers delve into the human brain with cutting-edge 'light imaging' technology
Ryan Thom and Matt Skibinski
Issue date: 10/18/07 Section: Features
The ability to detect your levels of stress, boredom or frustration may soon no longer fall on the shoulders of your close friends, family or psychiatrist. According to a group of seven Tufts researchers from the computer science and biomedical engineering departments, computers have the potential to read brain activity in ways that can be applied, at the very least, to improvements in work efficiency.
Tufts' Human Computer Interaction (HCI) group received a $450,000 grant from the National Science Foundation earlier this month after releasing a study that shows the feasibility of a method for computers to interpret brain activity in real time, using a cutting-edge, non-invasive form of brain-imaging technology known as functional near infrared spectroscopy (fNIRs).
The fNIRs consist of a small headband that users can wear while performing other activities - a stark contrast to MRI and other conventional brain-scanning technology, which requires users to be stationary, lying down or encased in large pieces of equipment.
"The way that this technology works, there is no limitation that forces it to be used in the lab," said Erin Solovey, a graduate student in the Computer Science Department who has been working on fNIRs research for over a year.
"You could have this on and have it attached to a PDA in your pocket," Solovey said. "That's the ideal situation, but right now we're still doing basic research to see how this technology might be used."
The device relies on "light imaging," a technique that uses light from optical fibers to illuminate the brain. Since most brain tissue is relatively transparent to this light, the fNIRs can sense differing levels of blood oxygenation that mark changes associated with neural activity. Light imaging has been around since the 1930s, but has only recently been applied to the brain through fNIRs.
While researchers said they can imagine a variety of potential applications for fNIRs technology, their research thus far has focused on whether or not the device can be used to determine a person's workload while performing a certain task. HCI recently published a research paper titled, "Human-Computer Interaction and Brain Measurement Using Functional Near-Infrared Spectroscopy" in which they demonstrated how fNIRs headband can detect when a person is being under- or over-worked.
Tufts' Human Computer Interaction (HCI) group received a $450,000 grant from the National Science Foundation earlier this month after releasing a study that shows the feasibility of a method for computers to interpret brain activity in real time, using a cutting-edge, non-invasive form of brain-imaging technology known as functional near infrared spectroscopy (fNIRs).
The fNIRs consist of a small headband that users can wear while performing other activities - a stark contrast to MRI and other conventional brain-scanning technology, which requires users to be stationary, lying down or encased in large pieces of equipment.
"The way that this technology works, there is no limitation that forces it to be used in the lab," said Erin Solovey, a graduate student in the Computer Science Department who has been working on fNIRs research for over a year.
"You could have this on and have it attached to a PDA in your pocket," Solovey said. "That's the ideal situation, but right now we're still doing basic research to see how this technology might be used."
The device relies on "light imaging," a technique that uses light from optical fibers to illuminate the brain. Since most brain tissue is relatively transparent to this light, the fNIRs can sense differing levels of blood oxygenation that mark changes associated with neural activity. Light imaging has been around since the 1930s, but has only recently been applied to the brain through fNIRs.
While researchers said they can imagine a variety of potential applications for fNIRs technology, their research thus far has focused on whether or not the device can be used to determine a person's workload while performing a certain task. HCI recently published a research paper titled, "Human-Computer Interaction and Brain Measurement Using Functional Near-Infrared Spectroscopy" in which they demonstrated how fNIRs headband can detect when a person is being under- or over-worked.
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