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Adaptive Markov process amplitude modeling was used to simulate and segment EEG signals. The least mean square adaptive algorithm was used to estimate the parameters of a first order Markov model. The coefficients of the model were utilized for EEG signal segmentation. The EEG signals were recorded from a controlled experimental setup of rodent brain injury with hypoxic-ischemic cardiac arrest. Results demonstrated that the proposed technique is a potential tool for EEG signal analysis.
Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint (Volume:1 )
Date of Conference: 2002