Fine-grained Temporal Attention Network for EEG-based Seizure Detection

Seungwoo Jeong, Eunjin Jeon, Wonjun Ko, Heung Il Suk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For patients who are suffering from epilepsy, how quickly and accurately detect seizures is an important issue. Electroencephalography (EEG) is one of the most widely-used measures for the seizure detection and thus has been used in many linear model/deep neural network-based methods. However, those existing EEG-based seizure detection methods have been hindered by limitations such as high latency and/or inconstant seizure detection ability. In this work, we propose an attention-based deep learning algorithm to handle these limitations. Further, the algorithm is learned in an end-to-end manner by combining a seizure EEG representation and a classification stage. To be specific, the proposed network exploits two encoder networks to represent seizure EEG. Then, with the attention mechanism, our network captures temporal interactions from the learned features. Finally, the proposed method efficiently and effectively identifies seizures. We demonstrate the validity of our proposed work by conducting classification of seizures using a publicly available CHB-MIT dataset. Further, we also compare the proposed network to other competitive state-of-the-art methods with an appropriate statistical analysis. Last but not least, we inspect the real-world usability of our method by estimating latency time.

Original languageEnglish
Title of host publication9th IEEE International Winter Conference on Brain-Computer Interface, BCI 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728184852
DOIs
Publication statusPublished - 2021 Feb 22
Event9th IEEE International Winter Conference on Brain-Computer Interface, BCI 2021 - Gangwon, Korea, Republic of
Duration: 2021 Feb 222021 Feb 24

Publication series

Name9th IEEE International Winter Conference on Brain-Computer Interface, BCI 2021

Conference

Conference9th IEEE International Winter Conference on Brain-Computer Interface, BCI 2021
Country/TerritoryKorea, Republic of
CityGangwon
Period21/2/2221/2/24

Keywords

  • Attention
  • Convolutional Neural Network
  • Deep Learning
  • Electroencephalography
  • Epilepsy
  • Seizure

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Signal Processing

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