Acquiring respiration rate from photoplethysmographic signal by recursive bayesian tracking of intrinsic modes in time-frequency spectra

Mikko Pirhonen, Mikko Peltokangas, Antti Vehkaoja

    Tutkimustuotos: ArtikkeliScientificvertaisarvioitu

    14 Sitaatiot (Scopus)
    34 Lataukset (Pure)

    Abstrakti

    Respiration rate (RR) provides useful information for assessing the status of a patient. We propose RR estimation based on photoplethysmography (PPG) because the blood perfusion dynamics are known to carry information on breathing, as respiration-induced modulations in the PPG signal. We studied the use of amplitude variability of transmittance mode finger PPG signal in RR estimation by comparing four time-frequency (TF) representation methods of the signal cascaded with a particle filter. The TF methods compared were short-time Fourier transform (STFT) and three types of synchrosqueezing methods. The public VORTAL database was used in this study. The results indicate that the advanced frequency reallocation methods based on synchrosqueezing approach may present improvement over linear methods, such as STFT. The best results were achieved using wavelet synchrosqueezing transform, having a mean absolute error and median error of 2.33 and 1.15 breaths per minute, respectively. Synchrosqueezing methods were generally more accurate than STFT on most of the subjects when particle filtering was applied. While TF analysis combined with particle filtering is a promising alternative for real-time estimation of RR, artefacts and non-respiration-related frequency components remain problematic and impose requirements for further studies in the areas of signal processing algorithms an PPG instrumentation.

    AlkuperäiskieliEnglanti
    Artikkeli1693
    JulkaisuSensors
    Vuosikerta18
    Numero6
    DOI - pysyväislinkit
    TilaJulkaistu - 1 kesäk. 2018
    OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

    Julkaisufoorumi-taso

    • Jufo-taso 1

    !!ASJC Scopus subject areas

    • Analytical Chemistry
    • Atomic and Molecular Physics, and Optics
    • Biochemistry
    • Instrumentation
    • Electrical and Electronic Engineering

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