Nonlinear system identification and analysis of complex dynamical behavior in reflected light measurements of vasomotion

摘要

Nonlinear system identification and analysis methods are employed to study the low-frequency oscillations present in time-series data obtained from reflectance imagery of microvasculature. Using the method of surrogate data testing the analysis reveals the deterministic nature of these oscillations believed by many to be chaotic. Further investigations by means of nonlinear system identification techniques indicate however that the underlying dynamics can described by a periodically driven nonlinear dynamical model exhibiting quasiperiodic behavior.