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Offers framework for nonlinear physiologic signals; extends adaptive methods but leaves open clinical validation.
We introduce a generic framework of dynamical complexity to understand and quantify fluctuations of physiologic time series. In particular, we discuss the importance of applying adaptive data analysis techniques, such as the empirical mode decomposition algorithm, to address the challenges of nonlinearity and nonstationarity that are typically exhibited in biological fluctuations.
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Peng et al. (2008) studied this question.
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