Newborn EEG simulation from nonlinear analysis

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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationProceedings - 8th International Symposium on Signal Processing and its Applications, ISSPA 2005
Pages191-194
Number of pages4
Volume1
DOIs
Publication statusPublished - 2005
Event8th International Symposium on Signal Processing and its Applications, ISSPA 2005 - Sydney, Australia
Duration: Aug 28 2005Aug 31 2005

Other

Other8th International Symposium on Signal Processing and its Applications, ISSPA 2005
CountryAustralia
CitySydney
Period8/28/058/31/05

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ASJC Scopus subject areas

  • Engineering(all)

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, pp. 191-194). [1580228] https://doi.org/10.1109/ISSPA.2005.1580228