Nonstationarity detection: The use of the cross correlation integral in ECG, and EEG profile analysis

Bunty B.E. Kiremire, Tshilidzi Marwala

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Citations (Scopus)

Abstract

This paper proposes the Stationarity Index, a measure of the similarities of the auto correlation integral of a section of a time series and the cross correlation of that section with others of the same time series. This measure of similarity is a measure of the stationarity of the time series and therefore can be used not only to detect nonstationarity but to also quantify it. The index is then successfully used in the analysis of electrocardiogram (ECG) and electroencephalogram (EEG) profiles to identify the changes in the dynamics of the signals as well as the occurrence of various events. The index displays sensitivity to changes in the dynamics exhibited in ECG signals that are the result of partial epileptic seizures, with the index going high in response to the changes in the dynamics.

Original languageEnglish
Title of host publicationProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Pages373-378
Number of pages6
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event1st International Congress on Image and Signal Processing, CISP 2008 - Sanya, Hainan, China
Duration: 27 May 200830 May 2008

Publication series

NameProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Volume5

Conference

Conference1st International Congress on Image and Signal Processing, CISP 2008
Country/TerritoryChina
CitySanya, Hainan
Period27/05/0830/05/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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