Modelling newborn EEG background using atime-varying fractional Brownian process

N. Stevenson*, L. Rankine, M. Mesbah, B. Boashash

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

A high quality model of newborn EEG background can aid in the analysis of newborn EEG. This paper proposes an improvement to the current time-varying, power-law spectrum model for newborn EEG background by using a band-limited fractional Brownian process with time-varying Hurst exponent. This model provides a more detailed definition of newborn EEG background than current models. The advantages of using a fractional Brownian process is that development of features for analysing newborn EEG background is inherent in the model and simulation of continuous newborn EEG background with variable spectral characteristics is simplified. The model is validated by showing that a fractional Brownian process is indeed a suitable model for newborn EEG background using the statistical properties of a fractional Brownian process and a database of 1080 epochs of newborn EEG background. A newborn EEG background simulation algorithm, based on discrete time-varying FIR filtering, is then presented.

Original languageEnglish
Title of host publication15th European Signal Processing Conference, EUSIPCO 2007 - Proceedings
Pages1246-1250
Number of pages5
Publication statusPublished - 2007
Externally publishedYes
Event15th European Signal Processing Conference, EUSIPCO 2007 - Poznan, Poland
Duration: Sept 3 2007Sept 7 2007

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491

Other

Other15th European Signal Processing Conference, EUSIPCO 2007
Country/TerritoryPoland
CityPoznan
Period9/3/079/7/07

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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