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Automated seizure detection in an EMU setting: Are software packages ready for implementation?

E E M Reus1, G H Visser1, J G van Dijk2

  • 1Department of Clinical Neurophysiology, Stichting Epilepsie Instellingen Nederland, the Netherlands.

Seizure
|January 18, 2022
PubMed
Summary

Automated seizure detection software shows high sensitivity but does not match expert technicians. Persyst software performed best among the evaluated tools for epilepsy monitoring.

Keywords:
Automatic detectionDetection softwareEMUEpilepsy monitoring unitVideo-EEG monitoring

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Area of Science:

  • Clinical Neurophysiology
  • Medical Device Technology
  • Epilepsy Diagnostics

Background:

  • Automated seizure detection software aims to improve the efficiency and accuracy of seizure identification in electroencephalography (EEG).
  • Evaluating the performance of commercial software packages is crucial for their effective implementation in clinical settings, such as epilepsy monitoring units (EMUs).

Purpose of the Study:

  • To assess the reliability of automated seizure detection using three commercial software packages (Persyst, Encevis, BESA) combined with live observation.
  • To compare the performance of these software packages against clinical physiologists' review in an EMU setting.

Main Methods:

  • Retrospective analysis of 286 prolonged EEG records from individuals aged 16-86 years.
  • Comparison of seizure detection sensitivity and false positive rates across Persyst, Encevis, and BESA software.
  • Reference standard included clinical reports and validated software detections.

Main Results:

  • Seizure detection sensitivity was high for all software (95-98% for detecting at least one seizure).
  • Persyst demonstrated the highest sensitivity (93%) for recognizing all seizures, followed by Encevis (88%) and BESA (84%).
  • Clinical physiologists achieved 100% sensitivity at record level and 98% at seizure level, with lower false positive rates than most software.

Conclusions:

  • Automated seizure detection software, while sensitive, does not outperform experienced clinical physiologists.
  • These tools can be valuable in EMUs when users understand their limitations.
  • Persyst software exhibited the strongest performance among the evaluated automated detection systems.