loading page

The Open Seizure Database Facilitating Research Into Non-EEG Seizure Detection
  • +2
  • Jamie Pordoy ,
  • Graham Jones ,
  • Nasser Matoorian ,
  • Nassim Dadashiserej ,
  • Massoud Zolgharni
Jamie Pordoy
university of West London

Corresponding Author:[email protected]

Author Profile
Graham Jones
Author Profile
Nasser Matoorian
Author Profile
Nassim Dadashiserej
Author Profile
Massoud Zolgharni
Author Profile


This research introduces the Open Seizure Database and Toolkit as a novel, publicly accessible resource designed to advance non-electroencephalogram seizure detection research. This paper highlights the scarcity of resources in the non-electroencephalogram domain and establishes the Open Seizure Database as the first openly accessible database containing multimodal sensor data from 49 participants in real-world, in-home environments. The database is comprised of 494 events, encompassing 146 epileptic seizures, collected over a duration of 453 days, presenting the most extensive publicly available non-electroencephalogram seizure data to date. Additionally, the database has 348 labelled false alarms, including 302 common human movements and activities. The Open Seizure Toolkit is designed to facilitate machine and deep learning practices by streamlining data from the Open Seizure Database. Utilising these resources, researchers can rapidly develop and train seizure detection models before deploying them to the Open Seizure Detector Android application. Access to these resources is expected to foster collaborative efforts, ultimately contributing to the establishment of a non-electroencephalogram gold standard and advancing the field of seizure detection.
Please view the OSDB at https://ieee-dataport.org/documents/open-seizure-database-v100