Epiness is based on brain activity rather than muscle movements or heart rate, and it will be a valuable device in the management of drug-resistant epilepsy.
FREMONT, CA: NeuroHelp, a spinoff company at Ben-Gurion University of the Negev (BGU), develops Epiness, the first wearable AI device that identifies and predicts epileptic seizures up to one hour before seizure onset through smartphone alert, which could be a valuable device in the management of drug-resistant epilepsy. This alarm devices offer real-time seizure detection but are unable to offer advanced warnings.
Epiness is a seizure prediction and detection tool based on a groundbreaking combination of EEG-based monitoring of brain activity together with machine-learning algorithms. The device combines a wearable electroencephalogram device with software that minimizes the number of EEG electrodes and optimizes placement on the scalp. The algorithms filter noise that is not connected to brain activity, extract measures of the underlying brain dynamics, and identify between brain activity before an expected epileptic seizure and when a seizure is not expected.
Up to 30 percent of epilepsy patients do not adequately respond to drugs and live with the fear of impending seizures. A viable seizure prediction device could offer a substantial betterment in quality of life for such people, enabling them to avoid seizure-related injuries. Epiness was created by Dr. Oren Shriki and his team at the BGU Department of Cognitive and Brain Sciences at the Inter-faculty Brain Science School. NeuroHelp was established by BGN Technologies, the BGU technology transfer company, and Dr. Shriki, its scientific founder.
Epileptic seizures expose patients to preventable hazards like falls, burns, and other injuries. Presently there are no seizure-predicting devices that can alert patients and enable them to prepare for upcoming seizures. Epiness will be both accurate and user-friendly since the algorithms reduce the number of EEG electrodes necessary. NeuroHelp has won first prize in the SilicoNegev startup competition, a significant recognition of this technology's outstanding ability, which is based on a combination of brain research and artificial intelligence.