Newborn EEG seizure detection using signal structural complexity

L. Rankine; M. Mesbah; B. Boashash

Newborn EEG seizure detection using signal structural complexity

L. Rankine, M. Mesbah, B. Boashash

Electrical and Computer Engineering

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

Abstract

A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time-frequency dictionary, is shown to be an adequate technique for detecting changes in signal structure. Changes are detected by using a new signal measure referred to as structural complexity, which is directly related to the dictionary being used for decomposition. The structural complexity measured is then incorporated in the proposed automatic newborn seizure detection algorithm.

Original language	English
Title of host publication	2004 12th European Signal Processing Conference, EUSIPCO 2004
Publisher	European Signal Processing Conference, EUSIPCO
Pages	2207-2210
Number of pages	4
Volume	06-10-September-2004
ISBN (Electronic)	9783200001657
Publication status	Published - Apr 3 2015
Event	12th European Signal Processing Conference, EUSIPCO 2004 - Vienna, Austria Duration: Sep 6 2004 → Sep 10 2004

Other

Other	12th European Signal Processing Conference, EUSIPCO 2004
Country	Austria
City	Vienna
Period	9/6/04 → 9/10/04

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

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title = "Newborn EEG seizure detection using signal structural complexity",

abstract = "A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time-frequency dictionary, is shown to be an adequate technique for detecting changes in signal structure. Changes are detected by using a new signal measure referred to as structural complexity, which is directly related to the dictionary being used for decomposition. The structural complexity measured is then incorporated in the proposed automatic newborn seizure detection algorithm.",

author = "L. Rankine and M. Mesbah and B. Boashash",

year = "2015",

month = apr,

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language = "English",

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publisher = "European Signal Processing Conference, EUSIPCO",

note = "12th European Signal Processing Conference, EUSIPCO 2004 ; Conference date: 06-09-2004 Through 10-09-2004",

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T1 - Newborn EEG seizure detection using signal structural complexity

AU - Rankine, L.

AU - Mesbah, M.

AU - Boashash, B.

PY - 2015/4/3

Y1 - 2015/4/3

N2 - A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time-frequency dictionary, is shown to be an adequate technique for detecting changes in signal structure. Changes are detected by using a new signal measure referred to as structural complexity, which is directly related to the dictionary being used for decomposition. The structural complexity measured is then incorporated in the proposed automatic newborn seizure detection algorithm.

AB - A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time-frequency dictionary, is shown to be an adequate technique for detecting changes in signal structure. Changes are detected by using a new signal measure referred to as structural complexity, which is directly related to the dictionary being used for decomposition. The structural complexity measured is then incorporated in the proposed automatic newborn seizure detection algorithm.

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M3 - Conference contribution

AN - SCOPUS:84979877981

VL - 06-10-September-2004

SP - 2207

EP - 2210

BT - 2004 12th European Signal Processing Conference, EUSIPCO 2004

PB - European Signal Processing Conference, EUSIPCO

T2 - 12th European Signal Processing Conference, EUSIPCO 2004

Y2 - 6 September 2004 through 10 September 2004

ER -

Newborn EEG seizure detection using signal structural complexity

Abstract

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ASJC Scopus subject areas

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