Skip to main content

Part of the book series: Health Informatics ((HI))

Abstract

Biosignal monitoring and recording are an integral part of medical diagnosis and treatment control mechanism. These methods mark the transition from point oriented measures to continuous measures in medicine. This transition is much more appropriate to the dynamics of physiological regulation in health and disease. Modern approaches for sensor technology, for new analysis algorithms and for database technologies help to move this emerging area forward. Technical advances originating in computer technology, in consumer electronics and microtechnology can support these technological advances.

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 PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

8 Bibliography

  1. Akselrod S, Gordon D, Ubel FA, Shannon DC, Barger AC, Cohen RJ: Power spectrum analysis of heart rate fluctuations: a quantitative probe of beat-to-beat cardiovascular control. Science 213: 220–222, 1981.

    Article  PubMed  CAS  Google Scholar 

  2. Bunde A, Havlin S, Kantelhardt JW, Penzel T, Peter JH, Voigt K: Correlated and uncorrelated regions in heart-rate fluctuations during sleep. Phys. Rev. Lett. 85: 3736–3739, 2000.

    Article  PubMed  CAS  Google Scholar 

  3. Kemp B, Värri A, Rosa AC, Nielsen KD, Gade J: A simple format for exchange of digitized polygraphic recordings. Electroencephalography and Clinical Neurophysiology 82: 391–393, 1992.

    Article  PubMed  CAS  Google Scholar 

  4. Klösch G, Kemp B, Penzel T, Schlögl A, Gruber G, Herrmann W, Rappelsberger P, Trenker E, Hasan J, Värri A, Dorffner G: The SIESTA project polygraphic and clinical database. IEEE Engineering in Medicine and Biology 20(3): 51–57, 2001.

    Article  Google Scholar 

  5. Korhonen I, Ojaniemi J, Nieminen K, van Gils M, Heikelä A, Kari A: Building the IMPROVE data library. IEEE Engineering in Medicine and Biology 16: 25–32, 1997.

    Article  CAS  Google Scholar 

  6. Peng CK, Havlin S, Stanley HE, Goldberger AL: Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time-series. Chaos 5: 82–87, 1995.

    Article  PubMed  CAS  Google Scholar 

  7. Penzel T, Brandenburg U, Fischer J, Jobert M, Kurella B, Mayer G, Niewerth HJ, Peter JH, Pollmächer T, Schäfer T, Steinberg R, Trowitzsch E, Warmuth R, Weeß HG, Wölk C, Zulley J: Empfehlungen zur computergestützten Aufzeichnung und Auswertung von Polygraphien. Somnologie 2: 42–48, 1998.

    Article  Google Scholar 

  8. Penzel T, Brandenburg U, Peter JH: Langzeitregistrierung und Zeitreihenanalyse in der Inneren Medizin. Internist 38: 734–741, 1997.

    Article  PubMed  CAS  Google Scholar 

  9. Penzel T, Kemp B, Klösch G, Schlögl A, Hasan J, Värri A, Korhonen I: Acquisition of biomedical signals databases. IEEE Engineering in Medicine and Biology 20(3): 25–32, 2001.

    Article  CAS  Google Scholar 

  10. Penzel T, McNames J, de Chazal P, Raymond B, Murray A, Moody G: Systematic comparison of different algorithms for apnoea detection based on electrocardiogram recordings. Med. Biol. Eng. Comput. 40: 402–407, 2002.

    Article  PubMed  CAS  Google Scholar 

  11. Schlögl A, Kemp B, Penzel T, Kunz D, Himanen S-L, Värri A, Dorffner G, Pfurtscheller G: Quality control of polysomnographic sleep data by histogram and entropy analysis. Clin. Neurophysiol. 110: 2165–2170, 1999.

    Article  PubMed  Google Scholar 

  12. Taqqu MS, Teverovsky V, Willinger W: Estimators for long-range dependence: an empirical study. Fractals 3: 785–798, 1995.

    Article  Google Scholar 

  13. Task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology: Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Circulation 93: 1043–1065, 1996.

    Google Scholar 

  14. Tompkins WJ: Biomedical Digital Signal Processing. Englewood Cliffs, Prentice-Hall, 1993.

    Google Scholar 

  15. Värri A, Kemp B, Penzel T, Schlögl A: Standards for biomedical signal databases. IEEE Engineering in Medicine and Biology 20(3): 33–37, 2001.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag London Limited

About this chapter

Cite this chapter

Penzel, T., Kesper, K., Becker, H.F. (2006). Biosignal Monitoring and Recording. In: Zieliński, K., Duplaga, M., Ingram, D. (eds) Information Technology Solutions for Healthcare. Health Informatics. Springer, London. https://doi.org/10.1007/1-84628-141-5_13

Download citation

  • DOI: https://doi.org/10.1007/1-84628-141-5_13

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-978-4

  • Online ISBN: 978-1-84628-141-9

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics