Abstract
Electroencephalography (EEG) is paramount for both retrospective analysis and real-time monitoring of epileptic seizures. Studies have shown that EEG-based seizure detection is very difficult for a specific epileptic population with intellectual disability due to the cerebral development disorders. In this work, a seizure detection method based on dynamic warping (DW) is proposed for patients with intellectual disability. It uses an EEG template of an individual subject's dominant seizure type, to extract the morphological features from EEG signals. A linear discriminant analysis (LDA) classifier is used to perform the seizure detection. Results show that the DW-based feature in the frequency domain is superior than that in the time domain, and the features extracted using wavelet transform method.
Original language | English |
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Title of host publication | 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'16), 16-20 August 2016, Orlando, Florida |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 1010-1013 |
Number of pages | 4 |
ISBN (Electronic) | 978-1-4577-0220-4 |
DOIs | |
Publication status | Published - 18 Oct 2016 |
Event | 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016) - Disney’s Contemporary Resort , Orlando, United States Duration: 16 Aug 2016 → 20 Aug 2016 Conference number: 38 http://embc.embs.org/2016/ |
Conference
Conference | 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016) |
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Abbreviated title | EMBC 2016 |
Country | United States |
City | Orlando |
Period | 16/08/16 → 20/08/16 |
Internet address |
Keywords
- Electroencephalography
- Feature extraction
- Epilepsy
- Seizures
- Dynamic warping
- Patient monitoring