On the epilepsy monitoring unit (EMU) at Stichting Epilepsie Instellingen Nederland (SEIN) Heemstede, epilepsy patients are admitted for EEG and video registration. These patients are observed 24 hours a day by nurses who staff the observation room. In some cases seizures are missed or only recognized in a later stadium of the seizure. A tool is needed to help the nurses detect seizures more accurately and more rapidly.
Many articles are published about algorithms for seizure detection, yet still no method has been implemented for online use in clinical practice. Most algorithms are focussed on an on/off alarm, where false alarms might still be a problem. We believe that an additional trend display of some kind would be of great value for the EMU setting. Therefore, our focus will be on a trend display of certain features that could help the nurses to react more rapidly to seizures.
We performed a study to look into the performance of the ‘manual’ seizure detection in the current situation to objectify the needs and to be able to look at the improvement that could be made with automated detection of seizures. We are currently starting the trend display study and have completed the current ‘manual’ performance study.
Wednesday 21 October 2015, 16:30 - 17:30 h
Building Carré - room CR 3.718