Skip to main content

Treatment of Ventricular Assist Device Test Bench Data for Prediction of Failures and Improved Intrinsic Reliability

  • Conference paper
  • First Online:
Technological Innovation for Industry and Service Systems (DoCEIS 2019)

Abstract

This article regards over analytics of reliability of ventricular assist devices (VAD) used as therapy for advanced heart failure conditions in the face of malfunction related adverse events. This question directs research and the search for a solution proposal, even if prospective, but that promotes the longevity of these devices, increasing the intrinsic reliability. An “In Vitro” test bench is used to obtain variations of dynamic behavior over time; by means of a set of variables and the deviations (failures) compared between the standard and tested devices; since these devices are systems that vary in time. An intelligent systematics obtained through the automation of the test bench, using sensors and actuators to control the independent variables, and the data collection and analysis using the technologies present in the industry 4.0 completes the increase of the reliability of the VAD.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    INTERMACS - Interagency Registry for Mechanically Assisted Circulatory Support contemplates a database with a total of 22,866 patients who received a mechanical circulatory support device approved by the FDA. With registration from 06/23/2006 to 12/31/2016 of 185 participating hospitals.

References

  1. Magalhães, C.C., Serrano Jr., C.V., Consolim-Colombo, F.M., Nobre, F., Fonseca, F.A.H.: Tratado de Cardiologia SOCESP, 3rd edn. Manole, Barueri (2015)

    Google Scholar 

  2. Martins, M.A., Carrilho, F.J., Alves, V.F., Castilho, E.: Clínica Médica, Volume 2: Doenças Cardiovasculares, Doenças Respiratórias, Emergências e Terapia Intensiva, 2nd edn. Manole, Barueri (2015)

    Google Scholar 

  3. Moreira, M.V., Montenegro, S.T., Paola, A.A.V.: Livro-texto da Sociedade Brasileira de Cardiologia, 2nd edn. Manole, Barueri (2015)

    Google Scholar 

  4. Azeka, E., Jatene, M.B., Jatene, I.B., Horowitz, E.S.K., Branco,. K.C.: I Diretriz de Insuficiência Cardíaca (IC) e Transplante Cardíaco, no Feto, na Criança e em Adultos Com Cardiopatia Congênita, da Sociedade Brasileira de Cardiologia. Arq. Bras. Cardiol. 103, 144 (2014)

    Google Scholar 

  5. Chambers, D.C., et al.: The registry of the international society for heart and lung transplantation: thirty-fourth adult lung and heart-lung transplantation report—2017; focus theme: allograft ischemic time. J. Hear. Lung Transplant. 36(10), 1047–1059 (2017)

    Article  Google Scholar 

  6. Kirklin, J.K., et al.: Eighth annual INTERMACS report: special focus on framing the impact of adverse events. J. Hear. Lung Transplant. 36(10), 1080–1086 (2017)

    Article  Google Scholar 

  7. Faceli, K., Lorena, A.C., Gama, J., de Carvalho, A.C.P.L.F.: Inteligência Artificial - Uma Abordagem de Aprendizado de Máquina. LTC, Rio de Janeiro (2011)

    Google Scholar 

  8. Atoche, A.C., Marrufo, O.P.: Nuevas Tendencias en Sistemas Mecatrónicos. Ingeniería 15(2) (2011)

    Google Scholar 

  9. Dias, J.C., Dias, J.C., Barbosa, M., Miyagi, P.E., Filho, D.J.S.: In vitro test bench with intelligent behavior to ventricular assist devices. In: 15th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2018), vol. 1, pp. 127–134 (2018)

    Google Scholar 

  10. de Andrade, L.A.: Jogos Digitais, Cidade e (Trans)mídia: A Próxima Fase, Curitiba (2015)

    Google Scholar 

  11. Marquesone, R.: Big Data: Técnicas e tecnologias para extração de valor dos dados. Casa do Código, São Paulo (2016)

    Google Scholar 

Download references

Acknowledgements

The authors thanks FAPESP, CNPQ e CAPES for supporting this research.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Jeferson C. Dias , Jônatas C. Dias , Edinei Legaspe , Rodrigo Lima Stoeterau , Fabrício Junqueira , Newton Maruyama , Paulo E. Miyagi or Diolino J. Santos Filho .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dias, J.C. et al. (2019). Treatment of Ventricular Assist Device Test Bench Data for Prediction of Failures and Improved Intrinsic Reliability. In: Camarinha-Matos, L., Almeida, R., Oliveira, J. (eds) Technological Innovation for Industry and Service Systems. DoCEIS 2019. IFIP Advances in Information and Communication Technology, vol 553. Springer, Cham. https://doi.org/10.1007/978-3-030-17771-3_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-17771-3_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17770-6

  • Online ISBN: 978-3-030-17771-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics