• DocumentCode
    1621357
  • Title

    Identification of Vascular Dynamics and Estimation of the Cardiac Output Waveform from Wearable PPG Sensors

  • Author

    McCombie, D. ; Asada, H. ; Reisner, A.

  • Author_Institution
    Dept. of Mechanical Eng., MIT, Cambridge, MA
  • fYear
    2006
  • Firstpage
    3490
  • Lastpage
    3493
  • Abstract
    A method for estimating cardiovascular dynamics and cardiac output waveforms using signals derived from two PPG sensors is presented. The method employs a novel signal-processing algorithm known as Laguerre model blind system identification to identify the vascular dynamics associated with the measured PPG signals. A unique deconvolution method is then used with the identified Laguerre models to estimate the cardiac output waveform. Initial results implementing the method on data derived from a human subject is presented. Results show good agreement between the morphology of the estimated waveform and the typical morphology of the human cardiac output waveform
  • Keywords
    cardiovascular system; deconvolution; medical signal processing; stochastic processes; wearable computers; Laguerre model blind system identification; cardiac output estimation; cardiovascular dynamics; deconvolution; wearable PPG sensors; Biological system modeling; Biosensors; Cardiovascular system; Deconvolution; Equations; Finite impulse response filter; Mechanical sensors; Sensor systems; USA Councils; Wearable sensors; biomedical signal processing; non-invasive cardiovascular monitoring; system identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1617231
  • Filename
    1617231