A Smart Breath Analyzer for Monitoring Home Mechanical Ventilated Patients

  • Antonio Vincenzo RadognaEmail author
  • Simonetta Capone
  • Giuseppina Anna Di Lauro
  • Nicola Fiore
  • Valentina Longo
  • Lucia Giampetruzzi
  • Luca Francioso
  • Flavio Casino
  • Pietro Siciliano
  • Saverio Sabina
  • Carlo Giacomo Leo
  • Pierpaolo Mincarone
  • Eugenio Sabato
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 539)


In this work we developed a Smart Breath Analyzer device devoted to the tele-monitoring of exhaled air in patients suffering Chronic Obstructive Pulmonary disease (COPD) and home-assisted by mechanical ventilation. The device based on sensors allows remote monitoring of a patient during a ventilotherapy session, and transmit the monitored signals to health service unit by TCP/IP communication through a cloud remote platform. The aim is to check continuously the effectiveness of therapy and/or any state of exacerbation of the disease requiring healthcare. By preliminary experimental tests, the prototype was validated on a volunteer subject.


COPD Telemedicine Breath analyzer 



The Smart Breath Analyzer was developed inside the project ReSPIRO (Rete dei Servizi Pneumologici: Integration, Research and Open-innovation—Bando Aiuti a Sostegno Cluster Tecnologici Regionali, project cod. F29R1T8) founded by Apulia Region.


  1. 1.
    Postma, D.S., Bush, A., van den Berge, M.: Risk factors and early origins of chronic obstructive pulmonary disease—review. Lancet 385, 899–909 (2015)CrossRefGoogle Scholar
  2. 2.
    World Health Organization 2017: The top 10 causes of death (Fact sheet no 310).
  3. 3.
    Vestbo, J., Hurd, S.S., Agustí, A.G., Jones, P.W., Vogelmeier, C., Anzueto, A., Barnes, P.J., Fabbri, L.M., Martinez, F.J., Nishimura, M., Stockley, R.A., Sin, D.D., Rodriguez-Roisin, R.: Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease GOLD executive summary. Am. J. Respir. Crit. Care Med. 187(4), 347–365 (2013)CrossRefGoogle Scholar
  4. 4.
    Global initiative for chronic obstructive lung disease, pocket guide to COPD diagnosis, management, and prevention. A guide for Health Care Professionals. 2017 Report. © 2017 Global Initiative for Chronic Obstructive Lung Disease, IncGoogle Scholar
  5. 5.
    Dixon, L.C., Ward, D.J., Smith, J., Holmes, S., Mahadeva, R.: New and emerging technologies for the diagnosis and monitoring of chronic obstructive pulmonary disease: a horizon scanning review. Chronic Respir. Dis. 13(4), 321–336 (2016)CrossRefGoogle Scholar
  6. 6.
    Lange, P., Halpin, D.M., O’Donnell, D.E., MacNee, W.: Diagnosis, assessment, and phenotyping of COPD: beyond FEV1—review. Int. J. COPD 11 (Special Issue 1st World Lung Disease Summit) (2016)Google Scholar
  7. 7.
    Mathew, T.L., Pownraj, P., Abdulla, S., Pullithadathil, B.: Technologies for clinical diagnosis using expired human breath analysis. Diagnostics 5, 27–60 (2015)CrossRefGoogle Scholar
  8. 8.
    Amann, A., Miekisch, W., Schubert, J., Buszewski, B., Ligor, T., Jezierski, T., Pleil, J., Risby, T.: Analysis of exhaled breath for disease detection. Annu. Rev. Anal. Chem. 7, 455–482 (2014)CrossRefGoogle Scholar
  9. 9.
    Bofan, M., Mores, N., Baron, M., Dabrowska, M., Valente, S., Schmid, M., Trové, A., Conforto, S., Zini, G., Cattani, P., Fuso, L., Mautone, A., Mondino, C., Pagliari, G., D’Alessio, T., Montuschi, P.: Within-day and between-day repeatability of measurements with an electronic nose in patients with COPD. J. Breath Res. 7, 017103 (8 pp.) (2013)CrossRefGoogle Scholar
  10. 10.
    Shafiek, H., Fiorentino, F., Merino, J.L., López, C., Oliver, A., Segura, J. de Paul, I., Sibila, O., Agustí, A., Cosío, B. G.: Using the electronic nose to identify airway infection during COPD exacerbations. PLoS ONE 10(9), e0135199 (16 pp.) (2015)CrossRefGoogle Scholar
  11. 11.
    Schnabel, R.M., Boumans, M.L.L., Smolinska, A., Stobberingh, E.E., Kaufmann, R., Roekaerts, P.M.H.J., Bergmans, D.C.J.J.: Electronic nose analysis of exhaled breath to diagnose ventilator associated pneumonia. Respir. Med. 109, 1454–1459, (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Microelectronics and Microsystems (CNR-IMM)LecceItaly
  2. 2.Dedalo Solutions srlPeccioliItaly
  3. 3.Institute of Clinical Physiology (CNR-IFC)LecceItaly
  4. 4.Institute for Research on Population and Social Policies, National Research Council (IRPPS-CNR)BrindisiItaly
  5. 5.“A. Perrino” HospitalBrindisiItaly

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