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A Nonlinear Pattern Recognition Pipeline for PPG/ECG Medical Assessments

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Sensors (CNS 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 539))

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Abstract

In this contribution, an innovative platform for ECG assessment from PPG signals for automotive applications is presented. The platform we propose is based on an optical miniaturized probe coupling a LED emitter with a silicon photomultipliers (SiPM) detector. The optical probe is able to measure PPG signal from the palm of hands. The new nonlinear Pattern Recognition Pipeline we developed associate the “Diastolic phase” of the heart to a “Reaction” physical dynamic while the “Systolic phase” can be mathematically modelled having a “Diffusion” physical proprieties. Results show there is specific cross-correlation between ECG signal and first-derivative of processed PPG waveform for the same person.

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Author information

Authors and Affiliations

  1. STMicroelectronics—Automotive and Discretes Group—Central R&D, Catania, Italy

    Francesco Rundo, Salvatore Petralia, Giorgio Fallica & Sabrina Conoci

Authors
  1. Francesco Rundo
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  2. Salvatore Petralia
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  3. Giorgio Fallica
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  4. Sabrina Conoci
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Corresponding author

Correspondence to Francesco Rundo .

Editor information

Editors and Affiliations

  1. University of Catania, Catania, Italy

    Bruno Andò

  2. IFAC-CNR, Sesto Fiorentino, Florence, Italy

    Francesco Baldini

  3. University of Rome Tor Vergata, Rome, Italy

    Corrado Di Natale

  4. Department of Information Engineering (DII), University of Brescia, Brescia, Italy

    Vittorio Ferrari

  5. University of Catania, Catania, Italy

    Vincenzo Marletta

  6. Department of Chemistry, University of Florence, Sesto Fiorentino, Florence, Italy

    Giovanna Marrazza

  7. University of Palermo, Palermo, Italy

    Valeria Militello

  8. University of Padova, Padua, Italy

    Giorgia Miolo

  9. Sapienza University of Rome, Rome, Italy

    Marco Rossi

  10. Università Politecnica delle Marche (UNIVPM), Ancona, Italy

    Lorenzo Scalise

  11. IMM-CNR, Lecce, Italy

    Pietro Siciliano

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Rundo, F., Petralia, S., Fallica, G., Conoci, S. (2019). A Nonlinear Pattern Recognition Pipeline for PPG/ECG Medical Assessments. In: Andò, B., et al. Sensors. CNS 2018. Lecture Notes in Electrical Engineering, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-030-04324-7_57

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  • DOI: https://doi.org/10.1007/978-3-030-04324-7_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04323-0

  • Online ISBN: 978-3-030-04324-7

  • eBook Packages: EngineeringEngineering (R0)

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