Advertisement

A Nonlinear Pattern Recognition Pipeline for PPG/ECG Medical Assessments

  • Francesco RundoEmail author
  • Salvatore Petralia
  • Giorgio Fallica
  • Sabrina Conoci
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 539)

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.

Keywords

PPG ECG Pattern recognition 

References

  1. 1.
    Birse, R.M., Knowlden, P.E.: Oxford Dictionary of National Biography. Oxford, Blackwell (2004)Google Scholar
  2. 2.
    Oreggia D., Guarino S., Parisi A., Pernice R., Adamo G., Mistretta L., Di Buono P., Fallica G., Cino C. A. and Busacca A. C.. Physiological parameters measurements in a cardiac cycle via a combo PPG-ECG system. In: Proceedings of the AEIT International Annual Conference, pp. 1–6 (2015)Google Scholar
  3. 3.
    Reisner, A., et al.: Utility of the photoplethysmogram in circulatory monitoring. J. Am. Soc. Anesthesiol. 108(5), 950–958 (2008)CrossRefGoogle Scholar
  4. 4.
    Petralia, S., Conoci, S.: PCR technologies for point of care testing: progress and perspectives. ACS Sens. 2, 876–891 (2017)CrossRefGoogle Scholar
  5. 5.
    Mazzillo, M., Condorelli, G., Sanfilippo, D., Valvo, G., Carbone, B., Fallica, G., Billotta, S., Belluso, M., Bonanno, G., Cosentino, L., Pappalardo, A., Finocchiaro, P.: Silicon photomultiplier technology at STMicroelectronics. IEEE Trans. Nuclear Sci. 56, 2434–2442 (2015)CrossRefGoogle Scholar
  6. 6.
    Rundo, F., Conoci, S., Ortis, A. Battiato S.: An advanced bio-inspired PhotoPlethysmoGraphy (PPG) and ECG pattern recognition system for medical assessment. Sensors 18, 405 (2018)CrossRefGoogle Scholar
  7. 7.
    Kanzow, C., Yamashita, N., Fukushima, M.: Levenberg-Marquardt methods with strong local convergence properties for solving nonlinear equations with convex constraints. JCAM 172, 375–397 (2004)MathSciNetzbMATHGoogle Scholar
  8. 8.
    Rundo, F., Fallica, P.G., Conoci, S., Petralia, S., Mazzillo, M.C.: Processing of electrophysiological signals, IT patent no. 102017000081018Google Scholar
  9. 9.
    Rundo, F., Fallica, P.G., Conoci, S.: A method of processing electrophysiological signals, corresponding system, vehicle and computer program product, IT patent no. 102017000120714Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.STMicroelectronics—Automotive and Discretes Group—Central R&DCataniaItaly

Personalised recommendations