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Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform

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...

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Detalles Bibliográficos
Autores principales: Wu, Hau-Tieng, Wu, Han-Kuei, Wang, Chun-Li, Yang, Yueh-Lung, Wu, Wen-Hsiang, Tsai, Tung-Hu, Chang, Hen-Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909275/
https://www.ncbi.nlm.nih.gov/pubmed/27304979
http://dx.doi.org/10.1371/journal.pone.0157135
Descripción
Sumario: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.