Seizure detection using dynamic warping for patients with intellectual disability

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

3 Citaties (Scopus)
1 Downloads (Pure)

Uittreksel

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.
Originele taal-2Engels
Titel38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'16), 16-20 August 2016, Orlando, Florida
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's1010-1013
Aantal pagina's4
ISBN van elektronische versie978-1-4577-0220-4
DOI's
StatusGepubliceerd - 18 okt 2016
Evenement38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016) - Disney’s Contemporary Resort , Orlando, Verenigde Staten van Amerika
Duur: 16 aug 201620 aug 2016
Congresnummer: 38
http://embc.embs.org/2016/

Congres

Congres38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016)
Verkorte titelEMBC 2016
LandVerenigde Staten van Amerika
StadOrlando
Periode16/08/1620/08/16
Internet adres

Vingerafdruk

Electroencephalography
Discriminant analysis
Wavelet transforms
Classifiers
Monitoring

Citeer dit

Wang, L., Arends, J. B. A. M., Long, X., Wu, Y., & Cluitmans, P. J. M. (2016). Seizure detection using dynamic warping for patients with intellectual disability. In 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'16), 16-20 August 2016, Orlando, Florida (blz. 1010-1013). Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2016.7590873
Wang, L. ; Arends, J.B.A.M. ; Long, X. ; Wu, Y. ; Cluitmans, P.J.M. / Seizure detection using dynamic warping for patients with intellectual disability. 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'16), 16-20 August 2016, Orlando, Florida. Piscataway : Institute of Electrical and Electronics Engineers, 2016. blz. 1010-1013
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title = "Seizure detection using dynamic warping for patients with intellectual disability",
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.",
keywords = "Electroencephalography, Feature extraction, Epilepsy, Seizures, Dynamic warping, Patient monitoring",
author = "L. Wang and J.B.A.M. Arends and X. Long and Y. Wu and P.J.M. Cluitmans",
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Wang, L, Arends, JBAM, Long, X, Wu, Y & Cluitmans, PJM 2016, Seizure detection using dynamic warping for patients with intellectual disability. in 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'16), 16-20 August 2016, Orlando, Florida. Institute of Electrical and Electronics Engineers, Piscataway, blz. 1010-1013, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016), Orlando, Verenigde Staten van Amerika, 16/08/16. https://doi.org/10.1109/EMBC.2016.7590873

Seizure detection using dynamic warping for patients with intellectual disability. / Wang, L.; Arends, J.B.A.M.; Long, X.; Wu, Y.; Cluitmans, P.J.M.

38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'16), 16-20 August 2016, Orlando, Florida. Piscataway : Institute of Electrical and Electronics Engineers, 2016. blz. 1010-1013.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

TY - GEN

T1 - Seizure detection using dynamic warping for patients with intellectual disability

AU - Wang, L.

AU - Arends, J.B.A.M.

AU - Long, X.

AU - Wu, Y.

AU - Cluitmans, P.J.M.

PY - 2016/10/18

Y1 - 2016/10/18

N2 - 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.

AB - 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.

KW - Electroencephalography

KW - Feature extraction

KW - Epilepsy

KW - Seizures

KW - Dynamic warping

KW - Patient monitoring

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DO - 10.1109/EMBC.2016.7590873

M3 - Conference contribution

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Wang L, Arends JBAM, Long X, Wu Y, Cluitmans PJM. Seizure detection using dynamic warping for patients with intellectual disability. In 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'16), 16-20 August 2016, Orlando, Florida. Piscataway: Institute of Electrical and Electronics Engineers. 2016. blz. 1010-1013 https://doi.org/10.1109/EMBC.2016.7590873