Photo: PUNIT PARANJPE / AFP / Getty Images
Experts from the University of North Florida (UNF) and the Mayo Clinic managed to anticipate the seizures of patients with epilepsy by half an hour via measurements made using a bracelet.
For Dr. Mona Nasseri, Assistant Professor of Electrical Engineering at UNF, it is a gift of time that can offer the hope of a better life these patients, allowing them to take fast-acting medications or alter their activities to avoid such episodes.
The study, the university said in a statement released this week, found patterns when researchers compared physiological data collected by a monitoring device worn on the wrist with the actual time of a seizure.
By analyzing data, such as heart rate, body temperature, and movement, the researchers found that could have predicted most seizures about 30 minutes earlier of them happening.
Reliable forecasts are possible
These findings show that it is possible to provide reliable seizure prognoses without directly measuring brain activity, the university stressed.
“I have seen these patients and I know they need something like this. When they have many seizures that are resistant to drugs, they have to avoid so many activities. We look forward to helping them, ”said Nasseri.
The study is part of the Epilepsy Foundation of the American Institute for Epilepsy Innovation and the My Seizure Gauge project, which includes international collaboration.
East is the first study that followed people during their daily activities for six to 12 months, rather than previous work that relied on recording patient data at the hospital, according to Nasseri.
They tracked six people with drug-resistant epilepsy who had a neurostimulation device implanted that monitors the electrical activity of the brain.
Due to the device in the brain, the researchers were able to receive data indicating exactly when the seizure occurred, rather than having to rely on participants to record the time in their personal diaries, which is less reliable.
The idea is to provide a warning when a seizure is imminent.
Nasseri is contributing to the study by implementation of signal processing and machine learning techniques to develop these seizure detection and prediction algorithms.
“We collected the data from the wrist devices and designed a machine learning algorithm,” he said. The project is based at the Mayo Clinic in Rochester, Minnesota, where Nasseri worked with Dr. Benjamin Brinkmann, the study’s principal investigator, before joining the UNF faculty in 2020.
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