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Cuffless Blood Pressure Estimation Based on Pulse Arrival Time Using Bio-impedance During Different Postures and Physical Exercises

  • Fatemeh HeydariEmail author
  • Malikeh Pour Ebrahim
  • Taiyang Wu
  • Katie Walker
  • Keith Joe
  • Jean-Michel Redouté
  • Mehmet Rasit Yuce
Conference paper
  • 34 Downloads
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)

Abstract

Cuffless blood pressure (BP) estimation using pulse arrival time (PAT) has become popular in recent years. There are several approaches to calculate PAT from various sensors placed on the body. In this chapter, the shoulder’s bio-impedance (BImp) signal is used as a surrogate together with ECG to estimate cuffless systolic BP (SBP) based on four different PAT readings. Different BP trends have been experimentally validated for varying postures and physical exercises. Data was collected from 43 participants in supine, sitting, or standing postures. Among all these participants, 26 were asked to undertake light, moderate, and heavy cycling on an exercise bike. SBP calculation results using each PAT calculation have been compared in terms of estimation accuracy. Overall, the results of SBP calculation with PAT obtained from the maximum value of the first derivative of BImp pulse signal are at least 2% more accurate than other methods.

Keywords

Blood pressure Pulse arrival Bio-impedance 

Notes

Acknowledgments

The authors would like to thank Dr. D. Buxi, previously working at the Biomedical Integrated Circuits and Sensors (BICS) Laboratory, Monash University, for preparing the prototype for the data collections. The authors would like to thank P. Howley and M. Hebblewhite from Planet Innovation for their help in organizing the data collection at Cabrini Health, and all participants for their collaboration and patience.

The work is supported by the Victorian Government through the Future Industry Fund Sector Growth Program Stream 1. M. R. Yuce’s work is supported by Australian Research Council Future Fellowships Grant FT130100430. The authors gratefully acknowledge the support of the Monash Institute of Medical Engineering for this project.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Fatemeh Heydari
    • 1
    Email author
  • Malikeh Pour Ebrahim
    • 1
  • Taiyang Wu
    • 1
  • Katie Walker
    • 2
  • Keith Joe
    • 2
  • Jean-Michel Redouté
    • 1
  • Mehmet Rasit Yuce
    • 1
  1. 1.Department of Electrical and Computer Systems EngineeringMonash UniversityMelbourneAustralia
  2. 2.Emergency DepartmentCabrini HealthMelbourneAustralia

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