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Medical students and nurses who listen to 15 seconds of single-channel sonified EEGs may detect seizures with 95% to 98% sensitivity, thus outperforming neurologists who review traditional visual EEG displays, according to the results of a single-center study published in the April issue of Epilepsia.
“Individuals without EEG training can detect ongoing seizures or seizurelike rhythmic and periodic patterns by merely listening to short clips of sonified EEG,” said Josef Parvizi, MD, PhD, Professor of Neurology at Stanford University Medical Center in California, and his associates. “Ours is also the first study to test the capability of a sonification method to detect a range of significant abnormalities when it is used by clinical staff (eg, physicians, nurses, and students).” 
The sonification technique is based on an algorithm that translates low-frequency EEG signals into “speechlike declamations,” the investigators said. Vocal pitch, loudness, and resonance vary depending on input. Unlike prior sonification methods, the new method conserves brain rhythms, rate, and seizure severity.
To test the method, 34 medical students and 30 nurses watched a four-minute training video before listening to 84 sonified EEGs, including seven seizures, 52 slowing or normal patterns, and 25 seizurelike abnormalities (ie, generalized periodic discharges, lateralized periodic discharges, triphasic waves, or burst suppression). For each patient, listeners heard two sonified EEG clips, one from each hemisphere, and designated them as “seizure,” “nonseizure,” or “don’t know.” For comparison, 12 EEG-trained neurologists and 29 EEG-trained medical students reviewed traditional visual displays of the same EEGs.
Using sonified EEGs, nurses identified seizures with a sensitivity of 95%, and medical students identified seizures with a sensitivity of 98%. In contrast, the sensitivity of visual displays was 88% when reviewed by neurologists and 76% when reviewed by EEG-trained medical students. Specificity of sonified EEGs was 85% when heard by the medical students and 82% when heard by the nurses. Specificity of traditional review was 90% for neurologists and 65% for medical students.
The study was based on a representative sample, not a prospectively and consecutively recruited cohort, which limits conclusions about how this technique might perform at the bedside, said the researchers. In addition, the sonification method would not identify focal seizures occurring outside the individual channels selected.
The study was funded by a Stanford University BioX Seed Grant. Dr. Parvizi and one coinvestigator invented the sonification method and cofounded a startup that has licensed the technology from Stanford University. The other two investigators had no conflicts of interest.
—Amy Karon
Suggested Reading
Parvizi J, Gururangan
Medical students and nurses who listen to 15 seconds of single-channel sonified EEGs may detect seizures with 95% to 98% sensitivity, thus outperforming neurologists who review traditional visual EEG displays, according to the results of a single-center study published in the April issue of Epilepsia.
“Individuals without EEG training can detect ongoing seizures or seizurelike rhythmic and periodic patterns by merely listening to short clips of sonified EEG,” said Josef Parvizi, MD, PhD, Professor of Neurology at Stanford University Medical Center in California, and his associates. “Ours is also the first study to test the capability of a sonification method to detect a range of significant abnormalities when it is used by clinical staff (eg, physicians, nurses, and students).”
The sonification technique is based on an algorithm that translates low-frequency EEG signals into “speechlike declamations,” the investigators said. Vocal pitch, loudness, and resonance vary depending on input. Unlike prior sonification methods, the new method conserves brain rhythms, rate, and seizure severity.
To test the method, 34 medical students and 30 nurses watched a four-minute training video before listening to 84 sonified EEGs, including seven seizures, 52 slowing or normal patterns, and 25 seizurelike abnormalities (ie, generalized periodic discharges, lateralized periodic discharges, triphasic waves, or burst suppression). For each patient, listeners heard two sonified EEG clips, one from each hemisphere, and designated them as “seizure,” “nonseizure,” or “don’t know.” For comparison, 12 EEG-trained neurologists and 29 EEG-trained medical students reviewed traditional visual displays of the same EEGs.
Using sonified EEGs, nurses identified seizures with a sensitivity of 95%, and medical students identified seizures with a sensitivity of 98%. In contrast, the sensitivity of visual displays was 88% when reviewed by neurologists and 76% when reviewed by EEG-trained medical students. Specificity of sonified EEGs was 85% when heard by the medical students and 82% when heard by the nurses. Specificity of traditional review was 90% for neurologists and 65% for medical students.
The study was based on a representative sample, not a prospectively and consecutively recruited cohort, which limits conclusions about how this technique might perform at the bedside, said the researchers. In addition, the sonification method would not identify focal seizures occurring outside the individual channels selected.
The study was funded by a Stanford University BioX Seed Grant. Dr. Parvizi and one coinvestigator invented the sonification method and cofounded a startup that has licensed the technology from Stanford University. The other two investigators had no conflicts of interest.
—Amy Karon
Suggested Reading
Parvizi J, Gururangan
Medical students and nurses who listen to 15 seconds of single-channel sonified EEGs may detect seizures with 95% to 98% sensitivity, thus outperforming neurologists who review traditional visual EEG displays, according to the results of a single-center study published in the April issue of Epilepsia.
“Individuals without EEG training can detect ongoing seizures or seizurelike rhythmic and periodic patterns by merely listening to short clips of sonified EEG,” said Josef Parvizi, MD, PhD, Professor of Neurology at Stanford University Medical Center in California, and his associates. “Ours is also the first study to test the capability of a sonification method to detect a range of significant abnormalities when it is used by clinical staff (eg, physicians, nurses, and students).”
The sonification technique is based on an algorithm that translates low-frequency EEG signals into “speechlike declamations,” the investigators said. Vocal pitch, loudness, and resonance vary depending on input. Unlike prior sonification methods, the new method conserves brain rhythms, rate, and seizure severity.
To test the method, 34 medical students and 30 nurses watched a four-minute training video before listening to 84 sonified EEGs, including seven seizures, 52 slowing or normal patterns, and 25 seizurelike abnormalities (ie, generalized periodic discharges, lateralized periodic discharges, triphasic waves, or burst suppression). For each patient, listeners heard two sonified EEG clips, one from each hemisphere, and designated them as “seizure,” “nonseizure,” or “don’t know.” For comparison, 12 EEG-trained neurologists and 29 EEG-trained medical students reviewed traditional visual displays of the same EEGs.
Using sonified EEGs, nurses identified seizures with a sensitivity of 95%, and medical students identified seizures with a sensitivity of 98%. In contrast, the sensitivity of visual displays was 88% when reviewed by neurologists and 76% when reviewed by EEG-trained medical students. Specificity of sonified EEGs was 85% when heard by the medical students and 82% when heard by the nurses. Specificity of traditional review was 90% for neurologists and 65% for medical students.
The study was based on a representative sample, not a prospectively and consecutively recruited cohort, which limits conclusions about how this technique might perform at the bedside, said the researchers. In addition, the sonification method would not identify focal seizures occurring outside the individual channels selected.
The study was funded by a Stanford University BioX Seed Grant. Dr. Parvizi and one coinvestigator invented the sonification method and cofounded a startup that has licensed the technology from Stanford University. The other two investigators had no conflicts of interest.
—Amy Karon
Suggested Reading
Parvizi J, Gururangan