An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression

M. N. Van Dongen; A. Karapatis; L. Kros; O. H.J. Eelkman Rooda; R. M. Seepers; C. Strydis; C. I. De Zeeuw; F. E. Hoebeek; W. A. Serdijn

doi:10.1109/BioCAS.2014.6981773

An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression

M. N. Van Dongen
, A. Karapatis
, L. Kros
, O. H.J. Eelkman Rooda
, R. M. Seepers
, C. Strydis
, C. I. De Zeeuw
, F. E. Hoebeek
, W. A. Serdijn

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

7 Citations (Scopus)

Abstract

This paper presents the design and implementation of a real-time epilepsy detection filter that is suitable for closed-loop seizure suppression. The design aims to minimize the detection delay, while a reasonable average detection rate is obtained. The filter is based on a complex Morlet wavelet and uses an adaptive thresholding strategy for the seizure discrimination. This relatively simple configuration allows the algorithm to run on a cheap and readily available microprocessor prototyping platform. The performance of the filter is verified using both in vivo real-time measurements as well as simulations over a pre-recorded EEG dataset (29.75 hours with 1914 seizures). An average detection delay of 492 ms is achieved with a sensitivity of 96.03% and a specificity of 93.60%.

Original language	English
Title of host publication	IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	504-507
Number of pages	4
ISBN (Electronic)	9781479923465
DOIs	https://doi.org/10.1109/BioCAS.2014.6981773
Publication status	Published - 9 Dec 2014
Event	10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014 - Lausanne, Switzerland Duration: 22 Oct 2014 → 24 Oct 2014

Publication series

Series	IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings

Conference

Conference	10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014
Country/Territory	Switzerland
City	Lausanne
Period	22/10/14 → 24/10/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

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10.1109/BioCAS.2014.6981773

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Van Dongen, M. N., Karapatis, A., Kros, L., Eelkman Rooda, O. H. J., Seepers, R. M., Strydis, C., De Zeeuw, C. I., Hoebeek, F. E., & Serdijn, W. A. (2014). An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression. In IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings (pp. 504-507). Article 6981773 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BioCAS.2014.6981773

Van Dongen, M. N. ; Karapatis, A. ; Kros, L. et al. / An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression. IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 504-507 (IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings).

@inproceedings{44b95b221fcb478b9347d0d340013b63,

title = "An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression",

abstract = "This paper presents the design and implementation of a real-time epilepsy detection filter that is suitable for closed-loop seizure suppression. The design aims to minimize the detection delay, while a reasonable average detection rate is obtained. The filter is based on a complex Morlet wavelet and uses an adaptive thresholding strategy for the seizure discrimination. This relatively simple configuration allows the algorithm to run on a cheap and readily available microprocessor prototyping platform. The performance of the filter is verified using both in vivo real-time measurements as well as simulations over a pre-recorded EEG dataset (29.75 hours with 1914 seizures). An average detection delay of 492 ms is achieved with a sensitivity of 96.03\% and a specificity of 93.60\%.",

author = "\{Van Dongen\}, \{M. N.\} and A. Karapatis and L. Kros and \{Eelkman Rooda\}, \{O. H.J.\} and Seepers, \{R. M.\} and C. Strydis and \{De Zeeuw\}, \{C. I.\} and Hoebeek, \{F. E.\} and Serdijn, \{W. A.\}",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014 ; Conference date: 22-10-2014 Through 24-10-2014",

year = "2014",

month = dec,

day = "9",

doi = "10.1109/BioCAS.2014.6981773",

language = "English",

series = "IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings",

pages = "504--507",

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Van Dongen, MN, Karapatis, A, Kros, L , Eelkman Rooda, OHJ, Seepers, RM, Strydis, C , De Zeeuw, CI, Hoebeek, FE & Serdijn, WA 2014, An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression. in IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings., 6981773, Institute of Electrical and Electronics Engineers Inc., IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings, pp. 504-507, 10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014, Lausanne, Switzerland, 22/10/14. https://doi.org/10.1109/BioCAS.2014.6981773

An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression. / Van Dongen, M. N.; Karapatis, A.; Kros, L. et al.
IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 504-507 6981773 (IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings).

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

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AU - Van Dongen, M. N.

AU - Karapatis, A.

AU - Kros, L.

AU - Eelkman Rooda, O. H.J.

AU - Seepers, R. M.

AU - Strydis, C.

AU - De Zeeuw, C. I.

AU - Hoebeek, F. E.

AU - Serdijn, W. A.

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N2 - This paper presents the design and implementation of a real-time epilepsy detection filter that is suitable for closed-loop seizure suppression. The design aims to minimize the detection delay, while a reasonable average detection rate is obtained. The filter is based on a complex Morlet wavelet and uses an adaptive thresholding strategy for the seizure discrimination. This relatively simple configuration allows the algorithm to run on a cheap and readily available microprocessor prototyping platform. The performance of the filter is verified using both in vivo real-time measurements as well as simulations over a pre-recorded EEG dataset (29.75 hours with 1914 seizures). An average detection delay of 492 ms is achieved with a sensitivity of 96.03% and a specificity of 93.60%.

AB - This paper presents the design and implementation of a real-time epilepsy detection filter that is suitable for closed-loop seizure suppression. The design aims to minimize the detection delay, while a reasonable average detection rate is obtained. The filter is based on a complex Morlet wavelet and uses an adaptive thresholding strategy for the seizure discrimination. This relatively simple configuration allows the algorithm to run on a cheap and readily available microprocessor prototyping platform. The performance of the filter is verified using both in vivo real-time measurements as well as simulations over a pre-recorded EEG dataset (29.75 hours with 1914 seizures). An average detection delay of 492 ms is achieved with a sensitivity of 96.03% and a specificity of 93.60%.

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BT - IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings

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Van Dongen MN, Karapatis A, Kros L , Eelkman Rooda OHJ, Seepers RM, Strydis C et al. An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression. In IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 504-507. 6981773. (IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings). doi: 10.1109/BioCAS.2014.6981773

An implementation of a wavelet-based seizure detection filter suitable for realtime closed-loop epileptic seizure suppression

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