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Medical & Biological Engineering & Computing

, Volume 51, Issue 1–2, pp 233–242 | Cite as

Deriving respiration from photoplethysmographic pulse width

  • Jesús LázaroEmail author
  • Eduardo Gil
  • Raquel Bailón
  • Ana Mincholé
  • Pablo Laguna
Original Article

Abstract

A method for deriving respiration from the pulse photoplethysmographic (PPG) signal is presented. This method is based on the pulse width variability (PWV), and it exploits the respiratory information present in the pulse wave velocity and dispersion. It allows to estimate respiration signal from only a pulse oximeter which is a cheap and comfortable sensor. Evaluation is performed over a database containing electrocardiogram (ECG), blood pressure (BP), PPG, and respiratory signals simultaneously recorded in 17 subjects during a tilt table test. Respiratory rate estimation error is computed obtaining of 1.27 ± 7.81 % (0.14 ± 14.78 mHz). For comparison purposes, we have also obtained a respiratory rate estimation from other known methods which involve ECG, BP, or also PPG signals. In addition, we have also combined respiratory information derived from different methods which involve only PPG signal, obtaining a respiratory rate error of −0.17 ± 6.67 % (−2.16 ± 12.69 mHz). The presented methods, PWV and combination of PPG derived respiration methods, avoid the need of ECG to derive respiration without degradation of the obtained estimates, so it is possible to have reliable respiration rate estimates from just the PPG signal.

Keywords

Photoplethysmography PPG-derived respiration Respiratory frequency Respiratory system Robustness Signal synthesis 

Notes

Acknowledgments

This work is supported by Universidad de Zaragoza under fellowship PTAUZ-2011-TEC-A-003, Ministerio de Ciencia y Tecnología, Spain, FEDER; under project TEC2010-21703-C03-02, by CIBER-BBN through Instituto de Salud Carlos III, by ARAID and Ibercaja under Programa de APOYO A LA I+D+i and by Grupo Consolidado GTC from DGA.

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Copyright information

© International Federation for Medical and Biological Engineering 2012

Authors and Affiliations

  • Jesús Lázaro
    • 1
    • 2
    Email author
  • Eduardo Gil
    • 1
    • 2
  • Raquel Bailón
    • 1
    • 2
  • Ana Mincholé
    • 1
    • 2
  • Pablo Laguna
    • 1
    • 2
  1. 1.Communications Technology Group (GTC), Aragón Institute of Engineering Research (I3A), IIS AragónUniversidad de ZaragozaZaragozaSpain
  2. 2.Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN)ZaragozaSpain

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