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Epileptic seizure detection based on video and EEG recordings

Aghaei, H ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1109/BIOCAS.2017.8325156
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2018
  4. Abstract:
  5. Clinical data from epileptic patients reveal important information about the characteristics of the particular type of epilepsy. Such data is often acquired in a bimodal fashion, e.g. video recordings are collected with the standard Electroencephalogram (EEG) data, in order to help the specialists validate their assessment based on one modality with the other. Manual annotation of the onset of seizures across several days' worth of data is time consuming. This paper proposes an automated epilepsy seizure detection method based on a combination of features from EEG and video data, and compares it against detectors using either modality alone. © 2017 IEEE
  6. Keywords:
  7. Electroencephalogram ; Spatial-temporal interest points ; Neurology ; Video recording ; Clinical data ; Electroencephalogram (EEG) datum ; Epilepsy ; Epileptic patients ; Epileptic seizure detection ; Manual annotation ; Seizure detection ; Spatial temporals ; Electroencephalography
  8. Source: 2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings, 19 October 2017 ; Volume 2018-January , 2018 , Pages 1-4 ; 9781509058037 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/8325156