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