Generalized Mean Phase Coherence for asynchrony abnormality detection in multichannel newborn EEG

Amir Omidvarnia, Sampsa Vanhatalo, Mostefa Mesbah, Ghasem Azemi, Paul Colditz, Boualem Boashash

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

1 Citation (Scopus)

Abstract

Inter-hemispheric asynchrony within the multichannel recordings of newborn EEG is associated with abnormal functionality of the newborn brain. Mean Phase Coherence (MPC) as a bivariate phase synchrony measure is widely used for pair-wise comparisons of scalp EEG phase information. A bivariate measure, however, is unlikely to capture the key feature of asynchrony seen in the sick neonatal brain, which is characterized by a global disruption of synchrony. In this study, the concept of cointegration is employed to generalize the bivariate MPC to deal with the multivariate case. The performance of the generalized MPC (GMPC) is evaluated using two simulated signals. It is also tested on a multichannel newborn EEG dataset with asynchronous inter-hemispheric bursts. The proposed method can be used to detect and quantify the degree of inter-hemispheric asynchrony from EEG signals.

Original languageEnglish
Title of host publication2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012
Pages274-279
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012 - Montreal, QC, Canada
Duration: Jul 2 2012Jul 5 2012

Other

Other2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012
CountryCanada
CityMontreal, QC
Period7/2/127/5/12

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ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing

Cite this

Omidvarnia, A., Vanhatalo, S., Mesbah, M., Azemi, G., Colditz, P., & Boashash, B. (2012). Generalized Mean Phase Coherence for asynchrony abnormality detection in multichannel newborn EEG. In 2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012 (pp. 274-279). [6310559] https://doi.org/10.1109/ISSPA.2012.6310559