A distributed descriptor characterizing structural irregularity of EEG time series for epileptic seizure detection

Zhenning Mei, Xian Zhao, Hongyu Chen, Wei Chen

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaten (Scopus)

Samenvatting

This paper presents a novel descriptor aiming at anomaly detection in sequential data, like epileptic seizure detection with EEG time series. The descriptor is derived from the eigenvalue decomposition (EVD) of a Hankel-form data matrix generated from the raw time series. Simulation trials imply that the descriptor is capable of characterizing the structural aspect of a time series. In addition, we deploy the proposed descriptor as a feature extractor and apply it on Bonn Seizure Database which is widely used in seizure detection. The high accuracies on classification problems are comparable with the state-of-the-art so validate the effectiveness of our method.

Originele taal-2Engels
Titel40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's3386-3389
Aantal pagina's4
ISBN van elektronische versie978-1-5386-3646-6
DOI's
StatusGepubliceerd - 26 okt 2018
Evenement40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society= (EMBC 2018) - Hawaii Convention Center, Honolulu, Verenigde Staten van Amerika
Duur: 18 jul 201821 jul 2018
Congresnummer: 40
https://embc.embs.org/2018/

Congres

Congres40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society= (EMBC 2018)
Verkorte titelEMBC 2018
LandVerenigde Staten van Amerika
StadHonolulu
Periode18/07/1821/07/18
Internet adres

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