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AuthorOmidvarnia A.
AuthorVanhatalo S.
AuthorMesbah M.
AuthorAzemi G.
AuthorColditz P.
AuthorBoashash B.
Available date2022-05-31T19:01:38Z
Publication Date2012
Publication Name2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/ISSPA.2012.6310559
URIhttp://hdl.handle.net/10576/31930
AbstractInter-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.
Languageen
SubjectAbnormality detection
Asynchrony
Bivariate
Cointegration
Data sets
EEG signals
Key feature
Multi-channel
Multi-channel recording
Pair-wise comparison
Phase coherence
Phase information
Phase synchrony
Simulated signals
Information science
Model predictive control
Signal detection
TitleGeneralized Mean Phase Coherence for asynchrony abnormality detection in multichannel newborn EEG
TypeConference Paper
Pagination274-279
dc.accessType Abstract Only


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