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Quantification of depth of anesthesia by nonlinear time series analysis of brain electrical activity

Autor: Widman, G., Schreiber, T., Rehberg, B., Hoeft, A., Elger, C. E.

We investigate several quantifiers of the electroencephalogram (EEG) signal with respect to their ability to indicate depth of anesthesia. For 17 patients anesthetized with Sevoflurane, three established measures (two spectral and one based on the bi

Externí odkaz: http://arxiv.org/abs/nlin/0007027

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Nonlinear denoising of transient signals with application to event related potentials

Autor: Effern, A., Lehnertz, K., Schreiber, T., Grunwald, T., David, P., Elger, C. E.

We present a new wavelet based method for the denoising of {\it event related potentials} ERPs), employing techniques recently developed for the paradigm of deterministic chaotic systems. The denoising scheme has been constructed to be appropriate fo

Externí odkaz: http://arxiv.org/abs/physics/0001069

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A Robust Method for Detecting Interdependences: Application to Intracranially Recorded EEG

Autor: Arnhold, J., Grassberger, P., Lehnertz, K., Elger, C. E.

We present a measure for characterizing statistical relationships between two time sequences. In contrast to commonly used measures like cross-correlations, coherence and mutual information, the proposed measure is non-symmetric and provides informat

Externí odkaz: http://arxiv.org/abs/chao-dyn/9907013

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