AI tracks seizures in real time - Futurity

You are free to share this article under the Attribution 4.0 International license. Researchers have combined artificial intelligence with systems theory to develop a more efficient way to detect and accurately identify an epileptic seizure in real time. "Our technique allows us to get raw data, process it, and extract a feature that's more informative for the machine learning model to use," says Walter Bomela, a postdoctoral fellow in the lab of Jr-Shin Li, professor in the electrical and systems engineering department of the Washington University in St. Louis McKelvey School of Engineering. "The major advantage of our approach is to fuse signals from 23 electrodes to one parameter that can be efficiently processed with much less computing resources," Bomela says. In brain science, the current understanding of most seizures is that they occur when normal brain activity is interrupted by a strong, sudden hyper-synchronized firing of a cluster of neurons.