Researchers at Johns Hopkins have been working on a way to improve the precision and effectiveness of seizure controlling brain implants by trying to eliminate false positives that needlessly trigger electrical pulses.
Sridevi V. Sarma, an an assistant professor of biomedical engineering at Hopkins with a background in electrical engineering and computer science, led the team that developed new algorithms that so far have been tested on brain recordings taken from four drug-resistant epileptics. The hope is that soon this algorithm will be tested in implanted devices of real patients in a proper clinical study.
From a Hopkins press release:
In a study published recently in the journal Epilepsy & Behavior, Sarma’s team reported that its system yielded superior results, including flawless detection of actual seizures and up to 80 percent fewer alarms when a seizure was not occurring. Although the testing was not conducted on patients in a clinical setting, the results were promising.
Further fine-tuning is under way, using brain recordings from more than 100 epilepsy patients at Johns Hopkins Hospital, where several epilepsy physicians have joined in the research. Sarma said that within two to four years she hopes to see her system incorporated into a brain implant that can be tested on people with drug-resistant epilepsy.
Sarma’s team compared electrical data from the brains of epilepsy patients before, during and after seizures. The researchers looked at how this activity changed over time, particularly when a seizure began. “We wanted to figure out when would be the optimal time to step in with treatment to stop the seizure,” she said. The team members “trained” their system to look for that moment without setting off false alarms.
Press release: New Early Warning System for Seizures Could Lead to Fewer False Alarms…
Article in Epilepsy & Behavior: Quickest detection of drug-resistant seizures: An optimal control approach…
