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)

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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

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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.

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Newborn EEG simulation from nonlinear analysis

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