Automatic characterization of dynamics in Absence Epilepsy

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Automatic characterization of dynamics in Absence Epilepsy. / Petersen, Katrine N.H.; Nielsen, Trine N.; Kjaery, Troels W.; Thomsen, Carsten E.; Sorensen, Helge B.D.

35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. IEEE, 2013. p. 4283-4286 FrD01.23.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Petersen, KNH, Nielsen, TN, Kjaery, TW, Thomsen, CE & Sorensen, HBD 2013, Automatic characterization of dynamics in Absence Epilepsy. in 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013., FrD01.23, IEEE, pp. 4283-4286, Annual International Conference of the IEEE 2013, Osaka, Japan, 03/07/2013. https://doi.org/10.1109/EMBC.2013.6610492

APA

Petersen, K. N. H., Nielsen, T. N., Kjaery, T. W., Thomsen, C. E., & Sorensen, H. B. D. (2013). Automatic characterization of dynamics in Absence Epilepsy. In 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 (pp. 4283-4286). [FrD01.23] IEEE. https://doi.org/10.1109/EMBC.2013.6610492

Vancouver

Petersen KNH, Nielsen TN, Kjaery TW, Thomsen CE, Sorensen HBD. Automatic characterization of dynamics in Absence Epilepsy. In 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. IEEE. 2013. p. 4283-4286. FrD01.23 https://doi.org/10.1109/EMBC.2013.6610492

Author

Petersen, Katrine N.H. ; Nielsen, Trine N. ; Kjaery, Troels W. ; Thomsen, Carsten E. ; Sorensen, Helge B.D. / Automatic characterization of dynamics in Absence Epilepsy. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. IEEE, 2013. pp. 4283-4286

Bibtex

@inproceedings{883f13b48dce4d4d938c3459b0442cea,
title = "Automatic characterization of dynamics in Absence Epilepsy",
abstract = "Dynamics of the spike-wave paroxysms in Childhood Absence Epilepsy (CAE) are automatically characterized using novel approaches. Features are extracted from scalograms formed by Continuous Wavelet Transform (CWT). Detection algorithms are designed to identify an estimate of the temporal development of frequencies in the paroxysms. A database of 106 paroxysms from 26 patients was analyzed. The database is large compared to other known studies in the field of dynamics in CAE. CWT is more efficient than the widely used Fourier transform due to CWTs ability to recognize smaller discontinuities and variations. The use of scalograms and the detection algorithms result in a potentially usable clinical tool for dividing CAE patients into subsets. Differences between the grouped paroxysms may turn out to be useful from a clinical perspective as a prognostic indicator or when adjusting drug treatment.",
author = "Petersen, {Katrine N.H.} and Nielsen, {Trine N.} and Kjaery, {Troels W.} and Thomsen, {Carsten E.} and Sorensen, {Helge B.D.}",
year = "2013",
doi = "10.1109/EMBC.2013.6610492",
language = "English",
pages = "4283--4286",
booktitle = "35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013",
publisher = "IEEE",
note = "null ; Conference date: 03-07-2013 Through 07-07-2013",

}

RIS

TY - GEN

T1 - Automatic characterization of dynamics in Absence Epilepsy

AU - Petersen, Katrine N.H.

AU - Nielsen, Trine N.

AU - Kjaery, Troels W.

AU - Thomsen, Carsten E.

AU - Sorensen, Helge B.D.

N1 - Conference code: 35

PY - 2013

Y1 - 2013

N2 - Dynamics of the spike-wave paroxysms in Childhood Absence Epilepsy (CAE) are automatically characterized using novel approaches. Features are extracted from scalograms formed by Continuous Wavelet Transform (CWT). Detection algorithms are designed to identify an estimate of the temporal development of frequencies in the paroxysms. A database of 106 paroxysms from 26 patients was analyzed. The database is large compared to other known studies in the field of dynamics in CAE. CWT is more efficient than the widely used Fourier transform due to CWTs ability to recognize smaller discontinuities and variations. The use of scalograms and the detection algorithms result in a potentially usable clinical tool for dividing CAE patients into subsets. Differences between the grouped paroxysms may turn out to be useful from a clinical perspective as a prognostic indicator or when adjusting drug treatment.

AB - Dynamics of the spike-wave paroxysms in Childhood Absence Epilepsy (CAE) are automatically characterized using novel approaches. Features are extracted from scalograms formed by Continuous Wavelet Transform (CWT). Detection algorithms are designed to identify an estimate of the temporal development of frequencies in the paroxysms. A database of 106 paroxysms from 26 patients was analyzed. The database is large compared to other known studies in the field of dynamics in CAE. CWT is more efficient than the widely used Fourier transform due to CWTs ability to recognize smaller discontinuities and variations. The use of scalograms and the detection algorithms result in a potentially usable clinical tool for dividing CAE patients into subsets. Differences between the grouped paroxysms may turn out to be useful from a clinical perspective as a prognostic indicator or when adjusting drug treatment.

U2 - 10.1109/EMBC.2013.6610492

DO - 10.1109/EMBC.2013.6610492

M3 - Article in proceedings

C2 - 24110679

AN - SCOPUS:84886550713

SP - 4283

EP - 4286

BT - 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013

PB - IEEE

Y2 - 3 July 2013 through 7 July 2013

ER -

ID: 213159340