Embrace’s seizure detection is based on an algorithm we’ve developed that is designed to recognize unusual movements, electrodermal activity variation and peripheral temperature.
Most devices on the market usually consider two threads of information: how strong and how long you’re moving. Instead Embrace takes into account additional variables, combining movement and electrodermal activity variations, that start when regions deep in your brain are activated in an atypical way (as with seizures). Our algorithm uses advanced machine learning methods, and it is trained on data collected in epilepsy monitoring units in hospitals in order to recognize the complex patterns of movements and electrodermal activity that are most likely to accompany a convulsive seizure.
We’ve recently implemented the Rest mode feature which allows Embrace users to switch Embrace to a higher sensitivity of seizure detection during the periods of limited movement; for example, when they're taking a nap, watching TV, reading a book, or sleeping. When in Rest Mode, Embrace will be able to pick up milder tonic clonic seizures.
To learn more about Embrace’s seizure detection algorithm we recommend this article: How accurate is Embrace’s seizure detection algorithm?
We encourage you to learn more about how the Embrace works.