PHASE SYNCHRONY DETECTION IN MULTICHANNEL NEWBORN EEG SIGNALS USING A MUTUAL INFORMATION BASED METHOD

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MOHAMMADI S.; AZEMI G.

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Journal: IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING Year:2015 | Volume:9 | Issue:3 Page(s): 215-227

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Title

PHASE SYNCHRONY DETECTION IN MULTICHANNEL NEWBORN EEG SIGNALS USING A MUTUAL INFORMATION BASED METHOD

Author(s)

MOHAMMADI S. | AZEMI G. | Issue Writer Certificate

Keywords

GENERALIZED PHASE SYNCHRONIZATIONQ2

GENERALIZED MUTUAL INFORMATIONQ2

INSTANTANEOUS PHASEQ2

NEWBORN EEGQ2

MULTIVARIATE SIGNALSQ2

Abstract

One of the most important NEWBORN EEG abnormalities is the synchrony between different channels which, according to the clinical studies, can lead to neurological and neurodevelopmental outcomes in adulthood. This paper introduces a new method for automated detection of phase synchrony in MULTIVARIATE SIGNALS with applications to NEWBORN EEG signals. In this method, first the INSTANTANEOUS PHASE of each channel of the signal is estimated using Hilbert transform. In the case of EEG signals, due to their multicomponent nature, components of the signal are needed to be extracted using a bank of band-pass filters. The synchronization between different channels of the signal is then quantitatively measured using a criterion based on the mutual information between INSTANTANEOUS PHASEs of the components of the signal. The proposed method in this paper is then used to analyze, from synchronization point of view, multichannel EEG signals acquired from 5 newborns which include seizure-nonseizure periods and burst-suppression (B-S) patterns. Reciever operating curves (ROCs) are used to illustrate the performance of the method. The performance of the proposed method is also compared with that of the existing one based on the cointegration concept. Experimental results prove that the proposed method outperforms the existing one in measuring the generalized phase synchrony in multichannel NEWBORN EEG signals. Also, results of analyzing seizure and nonseizure segments show that for all segmants there is a phase synchronization among EEG channels which is due to the connections between brain hemispheres in both cases. The results also show that seizure periods are more synchronous than nonseizure periods. The phase synchrony assessment of B-S patterns indicates that burst patterns are more synchronous than suppression patterns and there is a phase synchrony in both cases.

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APA: Copy

MOHAMMADI, S., & AZEMI, G.. (2015). PHASE SYNCHRONY DETECTION IN MULTICHANNEL NEWBORN EEG SIGNALS USING A MUTUAL INFORMATION BASED METHOD. IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING, 9(3), 215-227. SID. https://sid.ir/paper/81672/en

Vancouver: Copy

MOHAMMADI S., AZEMI G.. PHASE SYNCHRONY DETECTION IN MULTICHANNEL NEWBORN EEG SIGNALS USING A MUTUAL INFORMATION BASED METHOD. IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING[Internet]. 2015;9(3):215-227. Available from: https://sid.ir/paper/81672/en

IEEE: Copy

S. MOHAMMADI, and G. AZEMI, “PHASE SYNCHRONY DETECTION IN MULTICHANNEL NEWBORN EEG SIGNALS USING A MUTUAL INFORMATION BASED METHOD,” IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING, vol. 9, no. 3, pp. 215–227, 2015, [Online]. Available: https://sid.ir/paper/81672/en

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