The sugar cube-size NIST sensor can measure
human brain activity using a gas of rubidium atoms and micro-optics.
We first reported on an earlier iteration of the sensor, which has
been in development since 2004, back when the team was first able to
use the sensor to track a human heartbeat in 2010.
This week, the researchers report in the journal Biomedical Optics Express that their tiny sensor -- which consists of a gas of 100 billion rubidium atoms and fiber optics to detect the light signals that in turn register the strength of magnetic fields -- now uses a new type of optical fiber that improves signal clarity.
"We're focusing on making the sensors small, getting them close to the signal source, and making them manufacturable and ultimately low in cost," says NIST co-author Svenja Knappe in the institute's news release. "By making an inexpensive system, you could have one in every hospital to test for traumatic brain injuries and one for every football team."
The researchers hope the sensor will improve magnetoencephalography (MEG), a technique for measuring the magnetic fields produced by electrical activity in the brain. Applications include testing for traumatic brain injury, screening for visual perception in newborns, and mapping neurological activity before surgeries that, say, aim to treat epilepsy or remove tumors.
The current gold standard MEG is called a superconducting quantum interference device (SQUID), but it works best at just above absolute zero and thus requires heavy helmet-shaped flasks with cryogenic coolants. NIST's sensor, for one, might allow for lighter, cheaper, and less rigid helmets.
As with the tests to detect a human heartbeat, the team worked with German scientists at a lab in Berlin that is described as having the best magnetic shielding in the world to block the Earth's magnetic field from interfering with extremely sensitive measurements. (The sensor measures signals of about a trillionth of a tesla -- called a picotesla; MRIs, by comparison, register closer to 1 to 8 tesla.)
The team says it anticipates being able to improve its sensor's performance another tenfold by upping the amount of light it can detect.
We first reported on an earlier iteration of the sensor, which has
been in development since 2004, back when the team was first able to
use the sensor to track a human heartbeat in 2010.This week, the researchers report in the journal Biomedical Optics Express that their tiny sensor -- which consists of a gas of 100 billion rubidium atoms and fiber optics to detect the light signals that in turn register the strength of magnetic fields -- now uses a new type of optical fiber that improves signal clarity.
"We're focusing on making the sensors small, getting them close to the signal source, and making them manufacturable and ultimately low in cost," says NIST co-author Svenja Knappe in the institute's news release. "By making an inexpensive system, you could have one in every hospital to test for traumatic brain injuries and one for every football team."
The researchers hope the sensor will improve magnetoencephalography (MEG), a technique for measuring the magnetic fields produced by electrical activity in the brain. Applications include testing for traumatic brain injury, screening for visual perception in newborns, and mapping neurological activity before surgeries that, say, aim to treat epilepsy or remove tumors.
The current gold standard MEG is called a superconducting quantum interference device (SQUID), but it works best at just above absolute zero and thus requires heavy helmet-shaped flasks with cryogenic coolants. NIST's sensor, for one, might allow for lighter, cheaper, and less rigid helmets.
As with the tests to detect a human heartbeat, the team worked with German scientists at a lab in Berlin that is described as having the best magnetic shielding in the world to block the Earth's magnetic field from interfering with extremely sensitive measurements. (The sensor measures signals of about a trillionth of a tesla -- called a picotesla; MRIs, by comparison, register closer to 1 to 8 tesla.)
The team says it anticipates being able to improve its sensor's performance another tenfold by upping the amount of light it can detect.
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