Newborn EEG simulation from nonlinear analysis

L. Rankine; H. Hassanpour; M. Mesbah; B. Boashash

doi:10.1109/ISSPA.2005.1580228

Newborn EEG simulation from nonlinear analysis

L. Rankine^*, H. Hassanpour, M. Mesbah, B. Boashash

^*Corresponding author for this work

Electrical and Computer Engineering

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

2 Citations (Scopus)

Abstract

In this paper, we propose a novel method of simulating normal newborn EEG. The method is based on the results from the fractal dimension analysis of real EEG recordings. The fractal dimension analysis was done using the Higuchi method for fractal dimension estimation. Comparison of signals in the time domain, frequency domain and time-frequency domain between real and simulated signals show similarities validating the EEG simulator. This model can provide artefact free EEG signals for researchers so that algorithm parameters can be tuned or so that automatic EEG detection algorithms, such as seizure detection and epileptic spike detection, can be evaluated.

Original language	English
Title of host publication	Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005
Pages	191-194
Number of pages	4
Volume	1
DOIs	https://doi.org/10.1109/ISSPA.2005.1580228
Publication status	Published - 2005
Event	8th International Symposium on Signal Processing and its Applications, ISSPA 2005 - Sydney, Australia Duration: Aug 28 2005 → Aug 31 2005

Other

Other	8th International Symposium on Signal Processing and its Applications, ISSPA 2005
Country	Australia
City	Sydney
Period	8/28/05 → 8/31/05

ASJC Scopus subject areas

Engineering(all)

Access to Document

10.1109/ISSPA.2005.1580228

Fingerprint Dive into the research topics of 'Newborn EEG simulation from nonlinear analysis'. Together they form a unique fingerprint.

Cite this

Rankine, L, Hassanpour, H, Mesbah, M & Boashash, B 2005, Newborn EEG simulation from nonlinear analysis. in Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005. vol. 1, 1580228, pp. 191-194, 8th International Symposium on Signal Processing and its Applications, ISSPA 2005, Sydney, Australia, 8/28/05. https://doi.org/10.1109/ISSPA.2005.1580228

@inproceedings{95c96b3f372e4e22b05f0b8e8ddfdbb1,

title = "Newborn EEG simulation from nonlinear analysis",

abstract = "In this paper, we propose a novel method of simulating normal newborn EEG. The method is based on the results from the fractal dimension analysis of real EEG recordings. The fractal dimension analysis was done using the Higuchi method for fractal dimension estimation. Comparison of signals in the time domain, frequency domain and time-frequency domain between real and simulated signals show similarities validating the EEG simulator. This model can provide artefact free EEG signals for researchers so that algorithm parameters can be tuned or so that automatic EEG detection algorithms, such as seizure detection and epileptic spike detection, can be evaluated.",

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

year = "2005",

doi = "10.1109/ISSPA.2005.1580228",

language = "English",

isbn = "0780392434",

volume = "1",

pages = "191--194",

booktitle = "Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005",

note = "8th International Symposium on Signal Processing and its Applications, ISSPA 2005 ; Conference date: 28-08-2005 Through 31-08-2005",

}

TY - GEN

T1 - Newborn EEG simulation from nonlinear analysis

AU - Rankine, L.

AU - Hassanpour, H.

AU - Mesbah, M.

AU - Boashash, B.

PY - 2005

Y1 - 2005

N2 - In this paper, we propose a novel method of simulating normal newborn EEG. The method is based on the results from the fractal dimension analysis of real EEG recordings. The fractal dimension analysis was done using the Higuchi method for fractal dimension estimation. Comparison of signals in the time domain, frequency domain and time-frequency domain between real and simulated signals show similarities validating the EEG simulator. This model can provide artefact free EEG signals for researchers so that algorithm parameters can be tuned or so that automatic EEG detection algorithms, such as seizure detection and epileptic spike detection, can be evaluated.

AB - In this paper, we propose a novel method of simulating normal newborn EEG. The method is based on the results from the fractal dimension analysis of real EEG recordings. The fractal dimension analysis was done using the Higuchi method for fractal dimension estimation. Comparison of signals in the time domain, frequency domain and time-frequency domain between real and simulated signals show similarities validating the EEG simulator. This model can provide artefact free EEG signals for researchers so that algorithm parameters can be tuned or so that automatic EEG detection algorithms, such as seizure detection and epileptic spike detection, can be evaluated.

UR - http://www.scopus.com/inward/record.url?scp=33847134389&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33847134389&partnerID=8YFLogxK

U2 - 10.1109/ISSPA.2005.1580228

DO - 10.1109/ISSPA.2005.1580228

M3 - Conference contribution

AN - SCOPUS:33847134389

SN - 0780392434

SN - 9780780392434

VL - 1

SP - 191

EP - 194

BT - Proceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005

T2 - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005

Y2 - 28 August 2005 through 31 August 2005

ER -