Epilepsy can be very scary experiences for people who suffer from them, especially since they may sometimes result in the need for medical attention. Unfortunately, they often come on so fast that the people getting them aren’t able to get out a call for help beforehand – they simply have to ride out the seizure on their own, and hope for the best. Now, however, two new technologies may be able to help. One is a watch that alerts caregivers when it detects movements associated with seizures, while the other is a system that could stop seizures before they start, by sending electrical impulses to the brain.
A wearable alert device
The watch, known as the SmartWatch, is made by California-based tech company SmartMonitor. It can be worn 24 hours a day, and detects repetitive, excessive arm motions outside of the user’s regular movement spectrum, associated with grand mal seizures.If they are able to, wearers can send out an alert to family members or other caregivers of their choice, simply by pressing a button on the watch. If not, within 15 to 30 seconds the watch will automatically send a Bluetooth signal to the user’s Android smartphone (which can’t be any farther than five feet away), which will in turn send that same alert to the same people. False alarms can be cancelled with the press of a button.
A system to stop Epilepsy
At Baltimore’s Johns Hopkins University, meanwhile, assistant professor of biomedical engineering Sridevi V. Sarma is leading research into software that could more efficiently stop seizures before they happen.Currently, when people are prone to seizures that don’t respond to drug treatment, they sometimes have electrodes surgically implanted in their brains. Algorithms running in an accompanying electronics package monitor the brain’s electrical activity, and cause the electrodes to administer a electrical pulse to the brain, when seizure-like activity is detected.
The Johns Hopkins software is designed to work with systems like this, in which implanted electrodes deliver electrical pulses to a targeted location of the brain.Sarma and her team addressed this problem by analyzing the brain electrical activity of epilepsy patients, recorded before, during and after seizures. Specifically, they wanted to get a better idea of what sort of activity immediately preceded seizures. Once that activity was identified, they then trained their software to act only on it, while ignoring other types of activity that can confuse traditional systems.When tested on recordings of the brain activity of four epilepsy patients, the system easily detected all of the actual seizures, but produced up to 80 percent less false alarms than conventional technology.