Health
Wearable system designed to predict seizures
The drug helps control seizures in patients with epilepsy, but is less effective in other patients. The new system is designed to help the latter group, at least by notifying them when a seizure is likely to occur.
The Epines system, created by scientists at the University of Negeb Bengurion in Israel, is linked to an array of EEG (electroencephalogram) electrodes attached to the scalp that monitors electrical activity in the brain and performs machine learning-based machine learning. An algorithm that consists of two parts of a microprocessor. These algorithms were trained on EEG data from “large datasets” of epilepsy patients. This dataset was collected when both had and did not have a seizure.
By learning which patterns consistently occurred in the electrical activity immediately before the attack, the algorithm was finally able to predict their onset with 97% accuracy. The algorithm can also distinguish between the electrical signals of the brain and the distracting background “noise”. This means that only a few electrodes will eventually need to be used and the accuracy of the system will remain at 95%.
“Epileptic seizures put epileptic patients at a variety of preventable risks, including falls, burns, and other injuries,” says Chief Scientist Dr. Oren Schriki. “Therefore, we are very excited that the machine learning algorithms we have developed can accurately predict imminent seizures up to an hour before the seizures occur.”
Epiness technology is licensed to the further-developed Ben-Gurion spin-off company NeuroHelp. The plan is to evaluate the prototype in clinical trials later this year.
We are also working on a German consortium Seizure prediction earpiece, It detects a clear increase in the wearer’s pulse.
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