Nonlinear advanced methods for biological signal analysis

The estimation of nonlinear parameters in time series whose model is unknown has to consider the use of advanced analysis methods. The paper introduces time-domain indexes, monofractal characteristics (1/f^α spectrum, detrended fluctuation analysis) and a regularity statistic (approximate entropy). Multifractal approaches such as generalized structure functions have been also used to characterize the HRV signal. A determinism test on the time series assesses the presence of nonlinear structures by a hypothesis test based on surrogate data. In most cases, the multifractal spectrum of the original HRV series significantly differs (t-test), from those obtained from surrogate signals. Results in the HRV signal analysis confirm the presence of a nonlinear deterministic structure in time series. Moreover, nonlinear parameters can be used to separate normal subjects from patients suffering from cardiovascular diseases.