EMD based power spectral pattern analysis for quasi-brain-death EEG
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Dynamic extension of approximate entropy measure for brain-death EEG
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
Analysis of the quasi-brain-death EEG data based on a robust ICA approach
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
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The present study aims at the use of the translation errors of the EEG signals as criteria for brain death diagnosis. Since the EEG signals of the patients in coma or brain death contain several kinds of sources that differ from the viewpoint of determinism, we can exploit the difference of the translation errors for brain death diagnosis. We also show that the translation errors of the post-ICA EEG signals are more reliable than the ones of the pre-ICA EEG signals.