Seizure detection using dynamic warping for patients with intellectual disability

L. Wang; J.B.A.M. Arends; X. Long; Y. Wu; P.J.M. Cluitmans

doi:10.1109/EMBC.2016.7590873

Seizure detection using dynamic warping for patients with intellectual disability

L. Wang, J.B.A.M. Arends, X. Long, Y. Wu, P.J.M. Cluitmans

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

3 Citations (Scopus)

1 Downloads (Pure)

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
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	https://doi.org/10.1109/EMBC.2016.7590873
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)
Abbreviated title	EMBC 2016
Country	United States
City	Orlando
Period	16/08/16 → 20/08/16
Internet address	http://embc.embs.org/2016/

Keywords

Electroencephalography
Feature extraction
Epilepsy
Seizures
Dynamic warping
Patient monitoring

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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 (pp. 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. pp. 1010-1013

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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.",

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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, pp. 1010-1013, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016), Orlando, United States, 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. p. 1010-1013.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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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.

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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. p. 1010-1013 https://doi.org/10.1109/EMBC.2016.7590873