Our newest spike detection is described in this publication together with a study performed with independent data from the Danish Epilepsy Centre in Dianalund. An artificial intelligence-based EEG algorithm for detection of epileptiform EEG discharges: Validation against the diagnostic gold standard. With a sensitivity of 89%, the new encevis spike detection performs better than any previously published algorithm. If you want to try it on your own data, just contact us!

Listen to the podcast about encevis “Automating Spike and Seizure Detection” from Dick Moberg’s Neural Network! Our colleagues Ana Skupch and Franz Fürbass talk about the history and the future of encevis automated analysis of EEG.

A study on automated seizure detection in epilepsy monitoring units is presented in this paper: Improving staff response to seizures on the epilepsy monitoring unit with online EEG seizure detection algorithms. It shows how the encevis seizure detection detects seizures that are missed by the staff and thus improves the safety of the patients.

Check out the new article Applicability of NeuroTrend as a bedside monitor in the neuro ICU published in the Journal for Clinical Neurophysiology. It shows how easy it is to use encevis NeuroTrend and how suitable it is for the intensive care.