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-2 | Engels |
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Titel | 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 |
Plaats van productie | Piscataway |
Uitgeverij | Institute of Electrical and Electronics Engineers |
Pagina's | 3386-3389 |
Aantal pagina's | 4 |
ISBN van elektronische versie | 978-1-5386-3646-6 |
DOI's | |
Status | Gepubliceerd - 26 okt. 2018 |
Evenement | 40th 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. 2018 → 21 jul. 2018 Congresnummer: 40 https://embc.embs.org/2018/ |
Congres
Congres | 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 |
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Verkorte titel | EMBC 2018 |
Land/Regio | Verenigde Staten van Amerika |
Stad | Honolulu |
Periode | 18/07/18 → 21/07/18 |
Internet adres |