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.
@article{arxiv.1507.05943,
title = {Modeling the pulse signal by wave-shape function and analyzing by synchrosqueezing transform},
author = {Hau-tieng Wu and Han-Kuei Wu and Chun-Li Wang and Yueh-Lung Yang and Wen-Hsiang Wu and Tung-Hu Tsai and Hen-Hong Chang},
journal= {arXiv preprint arXiv:1507.05943},
year = {2016}
}