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Journal of Radio Electronics Online scientific journal · eISSN 1684-1719
2025, № 11 · BIOMEDICAL RADIO ELECTRONICS

Algorithm for automatic detection of sporadic epileptiform discharges in the early stage of development of delayed cerebral ischemia

I.A. Kershner1, M.V. Sinkin2, Y.V. Obukhov1, I.V. Okuneva2

1 Kotelnikov IRE RAS, Moscow, Russia
2 Sklifosovsky Research Institute for Emergency Medicine, Moscow, Russia
Full text DOI: 10.30898/1684-1719.2025.11.27 UDC 519.67 EDN ISBGLR

Abstract

An algorithm for automatic detection of delayed cerebral ischemia index during electroencephalographic monitoring of a patient after subarachnoid hemorrhage - dynamics of sporadic epileptiform discharges, has been developed. The algorithm is based on the analysis of the cross-correlation function of the electroencephalogram with a selected sample of epileptiform spike-wave discharge. The synchronization of channels located throughout the head was studied. The number of hourly epileptiform discharges was calculated both separately for the hemispheres - the left and the right, and for the zones of the brain - frontal, parietal and central. As a result of applying the algorithm, peak-wave discharges per hour clusters exceeding the threshold value and related in time are identified. The algorithm was applied to 14 control patients and 10 patients diagnosed with delayed cerebral ischemia. Sensitivity, accuracy, and selectivity of algorithm is equal to 90%, 83%, and 79% respectively.

  • electroencephalography
  • epileptiform discharges
  • correlation function
  • delayed cerebral ischemia
Аннотация (на русском)

Алгоритм автоматического детектирования спорадических эпилептиформных разрядов в ранней стадии развития церебральной отсроченной ишемии

Разработан алгоритм автоматического детектирования одного из индексов развития отсроченной церебральной ишемии при электроэнцефалографическом мониторинге пациента после субарахноидального кровоизлияния, им является динамика спорадических эпилептиформных разрядов. Алгоритм основан на анализе корреляционной функции электроэнцефалограммы с выбранным образцом эпилептиформного пик-волнового разряда. В результате применения алгоритма выделяются кластеры почасового количества пик-волновых разрядов, превышающих пороговое значение и связанных во времени.

For citation

Kershner I.A., Sinkin M.V., Obukhov Y.V., Okuneva I.V. Algorithm for automatic detection of sporadic epileptiform discharges in the early stage of development of delayed cerebral ischemia // Journal of Radio Electronics. – 2025. – No. 11. https://doi.org/10.30898/1684-1719.2025.11.27

References

  1. Muniz C.F. et al. Clinical development and implementation of an institutional guideline for prospective EEG monitoring and reporting of delayed cerebral ischemia // Journal of clinical neurophysiology. - 2016. - Т. 33. - №. 3. - С. 217-226.
  2. Rosenthal E.S. et al. Continuous electroencephalography predicts delayed cerebral ischemia after subarachnoid hemorrhage: a prospective study of diagnostic accuracy // Annals of neurology. - 2018. - Т. 83. - №. 5. - С. 958-969.
  3. Kim J.A. et al. High epileptiform discharge burden predicts delayed cerebral ischemia after subarachnoid hemorrhage // Clinical Neurophysiology. - 2022. - Т. 141. - С. 139-146.
  4. Dmitry M. et al. Application of frequency features of optical flow for event detection in video-EEG monitoring data // Journal of Biomedical Photonics & Engineering. - 2021. - Т. 7. - №. 3. - С. 30301.
  5. Zheng W.L. et al. Automated EEG-based prediction of delayed cerebral ischemia after subarachnoid hemorrhage // Clinical Neurophysiology. - 2022. - Т. 143. - С. 97-106.