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Portable Device Worn Like a Visor Detects Severe Stroke in Seconds

This new device, which is worn like a visor, can detect stroke in patients within seconds with a 92 percent accuracy, clinical investigators at the Medical University of South Carolina (MUSC) report.

The volumetric impedance phase shift spectroscopy (VIPS) device sends low energy radio waves through the brain that change frequency when passing though fluids. These waves are reflected back to through the brain and then detected by the device. When having a severe stroke, the brain’s fluids will change, then producing an asymmetry in the radio waves that are detected by the VIPS device. The greater the asymmetry is, the more severe the stroke.

Researchers hope this device will save valuable time, which is especially important in stroke. This will save a lot of time especially because the accuracy of the device simplifies the decision making process made by emergency personnel about where to take patients first.

“Transfer between hospitals takes a lot of time,” said Raymond D. Turner, M.D., professor of neurosurgery and chief of the Neuroscience Integrated Center of Clinical Excellence at MUSC. “If we can give the information to emergency personnel out in the field that this is a large-vessel occlusion, that should change their though process in triage as to which hospital they go to.”

The study’s goal was to have the device accurately identify severe stroke and then compare the results to established physical examination methods practiced by emergency personnel, like the Prehospital Acute Stroke Severity Scale.

Healthy participants as well as patients with suspected stroke were evaluated by emergency personnel using the VIPS device. The 30 second process took three readings that were taken and averaged, then patients were later taken and evaluated by neurologists who provided definitive diagnoses.

In comparison to neurologists’ diagnoses, the device displayed a 92 percent specificity. This holds the VIPS device above standard physical examination tools that are used by emergency personnel that only display specificity scores between 40 and 89 percent.

The VIPS device requires little training to operate, in comparison to what is required to learn in standard emergency examination skills. This overall reduces the possibility of human error during emergency diagnosis.

Researchers are now using the VITAL 2.0 study to determine if the VIPS device can use complex machine learning algorithms to teach itself how to discriminate between minor and severe stroke without the help of neurologists. This means the VIPS device could potentially have widespread clinical implications. Turner also predicts that the device has the potential to be used widely not only by emergency personnel, but also appear in other public spaces.


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