Skip to main content
SpringerLink
Log in

Development of an Algorithm and a Sensor to Monitor the Heart Rate by Volumetric Measurement Techniques

  • Conference paper
  • First Online:
Mobile Networks for Biometric Data Analysis

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 392))

Abstract

The person’s heart rate is an important indicator of their health status. A heart rate that is too high or too low could be a sign of several different diseases, such as a heart disorder, obesity, asthma, or many others. Many devices require users to wear the device on their chest or place a finger on the device. The approach presented in this paper describes the principle and implementation of a heart rate monitoring device, which is able to detect the heart rate with high precision with the sensor integrated in a wristband. One method to measure the heart rate is the photoplethysmogram technique. This method measures the change of blood volume through the absorption or reflection of light. A light emitting diode (LED) shines through a thin amount of tissue. A photo-diode registers the intensity of light that traverses the tissue or is reflected by the tissue. Since blood changes its volume with each heartbeat, the photo-diode detects more or less light from the LED. The device is able to measure the heart rate with a high precision, it has low performance and hardware requirements, and it allows an implementation with small micro-controllers.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
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.

    http://www.raspberrypi.org

  2. 2.

    http://www.arduino.cc/

References

  1. Martínez Fernández J, Augusto JC, Trombino G, Seepold R, Martínez Madrid N (2013) Self-aware trader: a new approach to safer trading, J Universal Comput Sc, 19(15): 2292–2319, ISSN: 0948-695X

    Google Scholar 

  2. Martínez J, Augusto JC, Seepold R,Madrid NM (2012) A sensor technology survey for a stress aware trading process, IEEE Trans Systems, Man and Cybernetics—Part C: Appl and Rev, ISSN: 1094-6977

    Google Scholar 

  3. Crowley OV, McKinley PS, Burg MM, Schwartz JE, Ryff CD, Weinstein M et al (2011) The interactive effect of change in perceived stress and trait anxiety on vagal recovery from cognitive challenge. Int J Psychophysiol 82:225–232

    Article  Google Scholar 

  4. Pan RL, Li JK (2007) A noninvasive parametric evaluation of stress effects on global cardiovascular function. Cardiovasc Eng 7:74–80

    Article  Google Scholar 

  5. Melillo P, Bracale M, Pecchia L (2011) Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination. BioMedical Eng OnLine 10:1–13

    Article  Google Scholar 

  6. Hjortskov N, Rissén D, Blangsted A, Fallentin N, Lundberg U, Søgaard K (2004) The effect of mental stress on heart rate variability and blood pressure during computer work. Eur J Appl Physiol 92:84–89

    Article  Google Scholar 

  7. Chandola T, Heraclides A, Kumari M (2010) Psychophysiological biomarkers of workplace stressors. Neurosci Biobehav Rev 35:51–57

    Article  Google Scholar 

  8. Scherz WD, Seepold R (2015) Physiologic parameter calculation supporting local and telemetric analysis. In: 6th Euro-pean Conference of the International Federation for Medical and Biological Engineering, International Federation for Medical and Biological Engineering (IFMBE), 45, ISSN 1680-0737

    Google Scholar 

  9. Einthoven W (1908) Weiteres über das Elektrokardiogram. Pflüger Arch. ges. Physiol, 517–548

    Google Scholar 

  10. Kohler B-U, Hennig C, Orglmeister R (2002) The principles of software QRS detection. IEEE Eng Med Biol Mag 21(1):42–57

    Article  Google Scholar 

  11. Polar RS800cx, Available: http://www.polar.com/en/products/maximize_performance/running_multisport/RS800CX, Cited Sept 2014

  12. Firstbeat Stress Monitoring, Available: http://www.firstbeattechnologies.com/index.php?page=3&sub_page=19&sub_page_2=93, Cited Sept 2014

  13. Stresseraser, Available: http://www.stresseraser-uk.com, Cited Sept 2014

  14. Mind Media, NeXus-10 MKII, http://www.mindmedia.info, Cited Sept 2014

  15. TSL2561, Available: https://learn.adafruit.com/tsl2561/overview, Cited May 2014

  16. Steven W, Smith (2014) The scientist and engineer’s guide to digital signal processing. online book 1997 Available: http://www.dspguide.com/, Cited Jul 2014

  17. Amidror I (2013) mastering the discrete fourier transform in one, two or several dimensions—pitfalls and artifacts. Springer

    Google Scholar 

  18. Smith JO (2014) Mathematics of the discrete fourier transform (DFT) with audio applications, online book 2007 Available: https://ccrma.stanford.edu/~jos/mdft/, Cited May 2014

  19. Rusch TL, Sankar R, Scharf JE (1996) Signal processing methods for pulse oximetry. Comput Biol Med 26:143–159

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Applied Sciences Konstanz, Brauneggerstr. 55, 78462, Konstanz, Germany

    Jens Gansloser & Ralf Seepold

Authors
  1. Jens Gansloser
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ralf Seepold
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jens Gansloser .

Editor information

Editors and Affiliations

  1. DIBET, Università Politecnica delle Marche Dipt di Ingegneria Biomed, Elettronica e, Ancona, Italy

    Massimo Conti

  2. Informatics, Reutlingen University, Reutlingen, Germany

    Natividad Martínez Madrid

  3. Computer Science / Ubiquitous Computing Lab, HTWG Konstanz, Konstanz, Germany

    Ralf Seepold

  4. Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche, Ancona, Italy

    Simone Orcioni

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Gansloser, J., Seepold, R. (2016). Development of an Algorithm and a Sensor to Monitor the Heart Rate by Volumetric Measurement Techniques. In: Conti, M., Martínez Madrid, N., Seepold, R., Orcioni, S. (eds) Mobile Networks for Biometric Data Analysis. Lecture Notes in Electrical Engineering, vol 392. Springer, Cham. https://doi.org/10.1007/978-3-319-39700-9_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-39700-9_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39698-9

  • Online ISBN: 978-3-319-39700-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation