Detection of newborns' EEG seizure using time-frequency divergence measures

Pega Zarjam; Ghasem Azemi; Mostefa Mesbah; Boualem Boashash

doi:10.1109/ICASSP.2004.1327139

Detection of newborns' EEG seizure using time-frequency divergence measures

Pega Zarjam, Ghasem Azemi, Mostefa Mesbah, Boualem Boashash

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

6 Citations (Scopus)

Abstract

In this paper, a time-frequency approach for detecting seizure activities in newborns Electroencephalogram (EEG) data is proposed. In this approach, the discrimination between seizure and non-seizure states is based on the time-frequency distance between the consequent segments in the EEG signal. Three different time-frequency measures and three different reduced time-frequency distributions are used in this study. The proposed method is tested on the EEG data acquired from three neonates with ages ranging from two days to two weeks. The experimental results validate the suitability of the proposed method in automated newborns' seizure detection. The results show an average seizure detection rate of 96% and false alarm rate of 5%.

Original language	English
Title of host publication	2004 IEEE International Conference on Acoustics, Speech and Signal Processing
Subtitle of host publication	Proceedings
Place of Publication	United States
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	4
Volume	V
ISBN (Print)	0780384849
DOIs	https://doi.org/10.1109/ICASSP.2004.1327139
Publication status	Published - 2004
Externally published	Yes
Event	2004 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Montreal, Canada Duration: 17 May 2004 → 21 May 2004

Conference

Conference	2004 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/Territory	Canada
City	Montreal
Period	17/05/04 → 21/05/04

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10.1109/ICASSP.2004.1327139

Cite this

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title = "Detection of newborns' EEG seizure using time-frequency divergence measures",

abstract = "In this paper, a time-frequency approach for detecting seizure activities in newborns Electroencephalogram (EEG) data is proposed. In this approach, the discrimination between seizure and non-seizure states is based on the time-frequency distance between the consequent segments in the EEG signal. Three different time-frequency measures and three different reduced time-frequency distributions are used in this study. The proposed method is tested on the EEG data acquired from three neonates with ages ranging from two days to two weeks. The experimental results validate the suitability of the proposed method in automated newborns' seizure detection. The results show an average seizure detection rate of 96\% and false alarm rate of 5\%.",

author = "Pega Zarjam and Ghasem Azemi and Mostefa Mesbah and Boualem Boashash",

year = "2004",

doi = "10.1109/ICASSP.2004.1327139",

language = "English",

isbn = "0780384849",

volume = "V",

booktitle = "2004 IEEE International Conference on Acoustics, Speech and Signal Processing",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2004 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP ; Conference date: 17-05-2004 Through 21-05-2004",

}

Zarjam, P, Azemi, G, Mesbah, M & Boashash, B 2004, Detection of newborns' EEG seizure using time-frequency divergence measures. in 2004 IEEE International Conference on Acoustics, Speech and Signal Processing: Proceedings. vol. V, Institute of Electrical and Electronics Engineers (IEEE), United States, 2004 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, Montreal, Quebec, Canada, 17/05/04. https://doi.org/10.1109/ICASSP.2004.1327139

Detection of newborns' EEG seizure using time-frequency divergence measures. / Zarjam, Pega; Azemi, Ghasem; Mesbah, Mostefa et al.
2004 IEEE International Conference on Acoustics, Speech and Signal Processing: Proceedings. Vol. V United States: Institute of Electrical and Electronics Engineers (IEEE), 2004.

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

TY - GEN

T1 - Detection of newborns' EEG seizure using time-frequency divergence measures

AU - Zarjam, Pega

AU - Azemi, Ghasem

AU - Mesbah, Mostefa

AU - Boashash, Boualem

PY - 2004

Y1 - 2004

N2 - In this paper, a time-frequency approach for detecting seizure activities in newborns Electroencephalogram (EEG) data is proposed. In this approach, the discrimination between seizure and non-seizure states is based on the time-frequency distance between the consequent segments in the EEG signal. Three different time-frequency measures and three different reduced time-frequency distributions are used in this study. The proposed method is tested on the EEG data acquired from three neonates with ages ranging from two days to two weeks. The experimental results validate the suitability of the proposed method in automated newborns' seizure detection. The results show an average seizure detection rate of 96% and false alarm rate of 5%.

AB - In this paper, a time-frequency approach for detecting seizure activities in newborns Electroencephalogram (EEG) data is proposed. In this approach, the discrimination between seizure and non-seizure states is based on the time-frequency distance between the consequent segments in the EEG signal. Three different time-frequency measures and three different reduced time-frequency distributions are used in this study. The proposed method is tested on the EEG data acquired from three neonates with ages ranging from two days to two weeks. The experimental results validate the suitability of the proposed method in automated newborns' seizure detection. The results show an average seizure detection rate of 96% and false alarm rate of 5%.

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DO - 10.1109/ICASSP.2004.1327139

M3 - Conference proceeding contribution

SN - 0780384849

VL - V

BT - 2004 IEEE International Conference on Acoustics, Speech and Signal Processing

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - United States

T2 - 2004 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP

Y2 - 17 May 2004 through 21 May 2004

ER -

Detection of newborns' EEG seizure using time-frequency divergence measures

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