For the roughly 50 million people worldwide with epilepsy, the exchange of electrical signals between cells in their brain can sometimes go haywire and cause a seizure—often with little to no warning. Two researchers at the University of Louisiana at Lafayette have developed a new AI-powered model that can predict the occurrence of seizures up to one hour before onset with 99.6 percent accuracy.
“Due to unexpected seizure times, epilepsy has a strong psychological and social effect on patients,” explains Hisham Daoud, a researcher who co-developed the new model.
Detecting seizures ahead of time could greatly improve the quality of life for patients with epilepsy and provide them with enough time to take action, he says. Notably, seizures are controllable with medication in up to 70 percent of these patients.
Daoud and his colleague Magdy Bayoumi are by no means the first people to explore ways to predict seizures. Other research groups have worked on ways to analyze brain activity using electroencephalogram (EEG) tests and have used the data to develop predictive models. However, each person exhibits unique brain patterns, which makes it hard to accurately predict seizures. Previous models were designed to do this in a two-stage process, where the brain patterns must be extracted manually and then a classification system is applied, which Daoud says adds complexity to the model.