Skip to main content
SpringerLink
Log in

Embedded Real-Time Heart Variability Analysis

  • Conference paper
4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007)

Part of the book series: IFMBE Proceedings ((IFMBE,volume 13))

Abstract

Heart Variability Analysis (HRV) is not suitable for real-time processing on a resource-limited, single sensor network node, such as a Body Sensor Network (BSN) node, due to the high sampling rate (> 200H z) required to digitise ECG signals and the non-preemtable nature of operating systems such as tinyOS. Both reasons combined dictate that the processing of each sample needs to be completed withing the inter-sample period, typically 5 msec for ECG signals. This paper discusses a dual-layer real-time heart variability analysis algorithm. The top layer is invoked every time a sample arrives. This layer includes a real-time algorithm that delineates the significant part of the ECG signal, the QRS complex. The second layer, is near real-time and is invoked only when a potential QRS is detected, at a significantly lower rate that corresponds to the person heart rate. This layer is responsible for detecting R peaks, estimating the interval between two successive peaks and performs heart rate variability analysis in the frequency domain.

Our system outperforms traditional ECG processing algorithms because the top layer completes well within the 5 msec sample inter-arrival period, ensuring that no samples are lost. The bottom layer can be delegated either to an underlying background task or a second processor. Because it is invoked less frequently than the top layer, it results in a lower interrupt rate, allowing for more flexible processing.

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 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

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.

References

  1. J. Dong, M. Xu, H. Zhu, and W. Lu. Wearable ECG Recognition and Monitor. In the 18th IEEE symposium on Computer-Based Medical Systems (CBMS’05), 2005.

    Google Scholar 

  2. L. Faes, G. Nollo, R. Antolini, F. Gaita, and F. Ravelli. A Method for Quantifying Atrial Fibrillation Organization Based on Wave-Morphology Similarity. IEEE Transactions on Biomedical Engineering, 49(12):1504–1513, 2002.

    Article  Google Scholar 

  3. J. Felblinger and E. Yvroud. Real Time Detection of Ventricular Fibrillation and its Use in a Semi-Automatic Defibrillator. Engineering in Medicine and Biology Society Vol.14. Proceedings of the Annual International Conference of the IEEE, 6, Nov. 1992.

    Google Scholar 

  4. R. Fensli, E. Gunnarson, and T. Gundersen. A wearable ecg-recording system for continuous arrythmia monitoring in a wireless tele-home-care situation. In the 18th IEEE symposium on Computer-Based Medical Systems (CBMS’05), Dublin, 2005.

    Google Scholar 

  5. EPSRC BiosensorNet: Autonomic Biosensor Networks for Pervasive Healthcare. http://ubimon.doc.ic.ac.uk/biosensornet/index.php?m=432.

    Google Scholar 

  6. S.L. Keoh, K. Twidle, N. Pryce, A.E. Shaeffer-Filho, E. Lupu, N. Dulay, M. Sloman, S. Heeps, S. Strowes, J. Sventek, and E. Katsiri. Policy-based management for body sensor networks. In submitted to BSN 2007, 2006.

    Google Scholar 

  7. B-U Kohler, C. Hennig, and R. Orglmeister. The principles of software qrs detection. IEEE Engineering in Medicine and Biology, pages 42–57, January/February 2002.

    Google Scholar 

  8. J. P. Martinez and S. Olmos R. Almeida. A Wavelet-Based ECG Delineator: Evaluation on Standard Databases. IEEE Transactions on Biomedical Engineering, 51(4):570–581, March 2004.

    Article  Google Scholar 

  9. V.A Nagin and S.V. Selishchev. Implementation of Algorithms for Identification of QRS-Complexes in Real-Time ecg Systems. Biomedical Engineering, 2001.

    Google Scholar 

  10. J. Pan and W. Tompkins. A real-time detection algorithm. IEEE Transactions of Biomedical Engineering, 1993.

    Google Scholar 

  11. A. Ruha, S. Sallinen, and S. Nissila. A real-time microprocessor qrs detection system with 1-ms timing accuracy for the measurement of ambulatory hrv. IEEE Transactions of Biomedical Engineering, 44, 1997.

    Google Scholar 

  12. S. R. Seydnejad and R. Kitney. Real-Time Heart Rate Variability Extraction Using the Kaiser Window. IEEE Transactions on Biomedical Engineering, 44(10):990–1005, 1997.

    Article  Google Scholar 

  13. M. P. Tulippo, T. H. Makikallio, T. E. S. Takala, T. Sepannen, and H. V. Huikuri. Quantitative beat-to-beat analysis of heart rate dynamics during exercise. In Computers in Cardiology. The American Physiological Society, Sep. 1997.

    Google Scholar 

  14. J. Welch, F. Guilak, and S. D. Baker. A wireless ECG Smart Sensor for Broad Aapplication in Life Threatening Event Detection. In the 26th Annual International Conference of the IEEE EMBS, 2001.

    Google Scholar 

  15. G.Z. Yang, editor. Body Sensor Networks. Springer, 2005.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computing, Imperial College London, 180, Queens Gate, SW7 2AZ, London, UK

    Eleftheria Katsiri, Lei Wang & Benny Lo

  2. Institute of Biomedical Engineering, Imperial College London, 180, Queens Gate, SW7 2AZ, London, UK

    Mel Ho & Chris Toumazou

Authors
  1. Eleftheria Katsiri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mel Ho
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Benny Lo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chris Toumazou
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Helmholtz Institute of Biomedical Engineering, RWTH Aachen University, Pauwelstr. 20, 52074, Aachen, Germany

    Steffen Leonhardt (Chair of Medical Information Technology) (Chair of Medical Information Technology)

  2. Connectivity Systems Group, Philips Research Europe, Weisshausstr. 2, 52066, Aachen, Germany

    Thomas Falck

  3. RWTH Aachen University, Kackertstr. 9, 52072, Aachen, Germany

    Petri Mähönen (Chair of Wireless Networks) (Chair of Wireless Networks)

Rights and permissions

Reprints and permissions

Copyright information

© 2007 International Federation for Medical and Biological Engineering

About this paper

Cite this paper

Katsiri, E., Ho, M., Wang, L., Lo, B., Toumazou, C. (2007). Embedded Real-Time Heart Variability Analysis. In: Leonhardt, S., Falck, T., Mähönen, P. (eds) 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007). IFMBE Proceedings, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70994-7_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-70994-7_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70993-0

  • Online ISBN: 978-3-540-70994-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation