  We apply the recently developed adaptive non-harmonic model based on the
wave-shape function, as well as the time-frequency analysis tool called
synchrosqueezing transform (SST) to model and analyze oscillatory physiological
signals. To demonstrate how the model and algorithm work, we apply them to
study the pulse wave signal. By extracting features called the spectral pulse
signature, {and} based on functional regression, we characterize the
hemodynamics from the radial pulse wave signals recorded by the
sphygmomanometer. Analysis results suggest the potential of the proposed signal
processing approach to extract health-related hemodynamics features.
