UL Lafayette researchers develop technology that can predict an epileptic seizure in a patient up to an hour before it happens with a 99 percent rate of accuracy.
Epileptic patients face a precarious life in which seizures can strike at any moment, often without warning. Dr. Magdy Bayoumi says their invention looks set to relieve a lot of stress.
“They can have a much better quality of life, and when they get a warning they can go to a medical facility, or use their treatment,” says Bayoumi.
Bayoumi says the easily portable detection system involves placing a detection device on a patient’s head that scans their brainwaves for suspicious activities.
“It reads the signal from the brain, analyzes the signal, and uses machine learning to be able to predict the seizure,” says Bayoumi.
Bayoumi says they haven’t figure out the best way yet to attach the device to a patient’s head, but suspects it will likely be via a headband or cap.
The device on the person’s head will sync up to an app that is accessible not just by the patient, but by anyone the patient wants to keep in the loop.
“The family members and so on will get a signal on their smartphone that their family member is expecting a seizure,” says Bayoumi.
The technology was tested on 22 patients at Boston Children’s Hospital, which produced the 99 percent rate of accuracy.
