Incorporating uncertainty in data labeling into detection of brain interictal epileptiform discharges from EEG using weighted optimization

Bahman Abdi-Sargezeh, Antonio Valentin, Gonzalo Alarcon, Saeid Sanei

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Interictal epileptiform discharges (IEDs) can have various morphologies as well as spatial distributions and sometimes are associated with other brain activities, resulting in uncertainty in their labeling. Such an uncertainty corresponds to the probability of a waveform being an IED. Here, we incorporate this probability in an IED detection system which combines spatial component analysis (SCA) with the IED probabilities referred to as SCA-IEDP-based method. For comparison, we also propose SCA-based method in which the probability of being IED is ignored. The outcome shows that the SCA-IEDP outperforms SCA.

Original languageEnglish
Pages (from-to)1000-1004
Number of pages5
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2021-June
DOIs
Publication statusPublished - 2021
Event2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Virtual, Toronto, Canada
Duration: 6 Jun 202111 Jun 2021

Keywords

  • IED detection
  • IED morphology
  • Interictal epileptiform discharges
  • Labeling with uncertainty
  • Tensor decomposition

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