New research shows that medical students and nurses—non-specialists, in other words—can listen to a new “brain stethoscope” and reliably detect so-called silent seizures—a neurological condition where patients have epileptic seizures without any of the associated physical convulsions.
When a doctor or nurse suspects something is wrong with a patient’s heart, there’s a simple way to check: use a stethoscope to hear the sounds it makes. Doctors and nurses can use the same diagnostic tool to figure out what’s going on with the heart, lungs, stomach, and more, but not the brain. The new device may change that.
Over the past several years, neurologists have been working with a specialist in computer music to develop the brain stethoscope—not a stethoscope per se, but rather an algorithm that translates the brain’s electrical activity into sounds.
“This technology will enable nurses, medical students, and physicians themselves to actually assess their patient right there and they will be able to determine if the patient is having silent seizures,” says Josef Parvizi, a professor of neurology and neurological sciences at Stanford University.
The desire for a brain stethoscope stems from a basic problem with treating epileptic seizures—namely, a great many of them may go undetected and untreated.
Technically, a seizure is a neurological problem, in which ordinarily calm electrical brain waves go haywire. That erratic activity can cause convulsions—but not always.
“You might think that all seizures must cause some sort of convulsions, namely a patient who’s having a seizure must fall down and shake on the ground. But that’s actually not the case, especially in critically ill patients in the intensive care units,” says Parvizi, who is also a member of Stanford Bio-X, the Stanford Neurosciences Institute, and the Child Health Research Institute.
“Close to 90 percent of those patients will have silent seizures,” and though not visible they can still damage the brain if they are prolonged.
On top of that, diagnosing silent seizures can be a drawn-out process, even during regular hours at a major hospital. First, a trained technician comes in, sets up sensors on a patient’s skull to record the brain’s electrical activity, then makes a recording and sends it to a neurology specialist for analysis. By the time the diagnosis comes in, hours may have passed. After hours or in smaller hospitals, the process can take even longer—for example, a technician may have to come from hours away just to set up the equipment.
“I had never even entertained the idea that we would attach some of my music synthesis to somebody’s head.”
The solution came, Parvizi says, after he watched the Kronos Quartet perform a piece of music based on data recorded by a scientific instrument aboard the Voyager space probe. Parvizi realized something similar could be done with brain waves, so he sent some data files to Chris Chafe, a professor of music at Stanford.
“I had never even entertained the idea that we would attach some of my music synthesis to somebody’s head,” says Chafe, who is also a member of Bio-X and the Neurosciences Institute.
But it wasn’t all that odd either. Chafe has also made music out of climate change data and the carbon dioxide generated by ripening tomatoes. In this case, he used brain-wave data to modulate the singing sounds of a computer-synthesized voice—a natural choice given the context.
“Once he sent me the files and I listened to them, I was literally in shock, because it was so intuitive,” Parvizi says. “You could hear the transition from non-seizure to seizure so easily, that I just basically picked up the phone and told Chris that we have something right here.”
95 percent accuracy
But Parvizi is a trained neurologist, and to really test the potential of a brain stethoscope he wanted to see if non-specialists could hear the difference between normal brain activity and a seizure.
So, medical student Kapil Gururangan and Babak Razavi, a clinical assistant professor of neurology, gathered 84 brain wave samples, called electroencephalograms or EEGs, 32 of which included either a seizure or some features typical of one. Then, they turned those samples into music using Chafe’s algorithm and played them for 34 medical students and 30 nurses.
Despite having no training in the diagnosis of epilepsy, medical students and nurses were remarkably good at discerning seizures and seizure-like events from normal brain waves.
“The ability of an untrained medical student or nurse to read an EEG is pretty dismal—it’s 50 percent,” Gururangan says. But by listening to that EEG transformed into sound, medical students and nurses could accurately detect seizures more than 95 percent of the time.
Medical students and nurses also correctly identified samples with seizure-like features about three-quarters of the time and they correctly identified normal activity at similar rates—not perfect, but not bad either, given their training, Gururangan says.
“The question now that we have to figure out is: How are actual physicians going to use this tool and how do physicians use this information in their decision-making?” Gururangan says.
The researchers report their findings in the journal Epilepsia.
Source: Stanford University
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