[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

Finite difference and lead field methods in designing implantable ECG monitor

  • Original Article
  • Published:
Medical and Biological Engineering and Computing Aims and scope Submit manuscript

Abstract

To minimize time-consuming and expensive in vitro and in vivo testing, information regarding the effects of implantation and the implants on measurements should be available during the designing of active implantable devices measuring bioelectric signals such as electrocardiograms (ECG). Modeling offers a fairly inexpensive and effective means of studying and demonstrating the effects of implantation on ECG measurements prior to any in vivo tests, and can thus provide the designer with valuable information. Finite difference model (FDM) and lead field approaches offer straightforward and effective modeling methods supporting the designing of active implantable ECG devices. The present study demonstrates such methods in developing and studying ECG implants. They were applied in demonstrating the effects of implant dimensions and of electrode implantation on the measurement sensitivity of the ECG device. The results of the simulations indicated that the interelectrode distance is the factor of the implant design determining the lead sensitivity. Other parameters related implant dimensions and shape have minor effect on the morphology of the ECG or on the average sensitivity of the measurement. This is shown for example when the interelectrode distance was reduced to 1/3 of original the average lead sensitivity decreased by 69.1% while larger relative changes in other dimensions produced clearly smaller changes. It was also observed here that implanting the electrodes deeper under the skin has major effects on the local sensitivities in heart muscle and thus affect to the morphology of the ECG. The study indicated also that non-conducting medium (i.e. implant insulated body) between the electrodes increases the sensitivity on heart muscle compared to cases where only electrodes are implanted.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Ackerman MJ (1991) The Visible Human Project. J Biocommun 18(2):14

    Google Scholar 

  2. Boersma L, Mont L, et al (2004) Value of the implantable loop recorder for the management of patients with unexplained syncope. Europace 6(1):70–76

    Article  Google Scholar 

  3. Carter EL Jr, Pollack SR, et al (1990) Theoretical determination of the current density distributions in human vertebral bodies during electrical stimulation. IEEE Trans Biomed Eng 37(6):606–614

    Article  Google Scholar 

  4. Chrysostomakis SI, Klapsinos NC, et al (2003) Sensing issues related to the clinical use of implantable loop recorders. Europace 5(2):143–148

    Article  Google Scholar 

  5. Farwell DJ, Freemantle N, et al (2004) Use of implantable loop recorders in the diagnosis and management of syncope. Eur Heart J 25(14):1257–1263

    Article  Google Scholar 

  6. Ferdjallah M, Bostick FX Jr, et al (1996) Potential and current density distributions of cranial electrotherapy stimulation (CES) in a four-concentric-spheres model. IEEE Trans Biomed Eng 43(9):939–943

    Article  Google Scholar 

  7. Gabriel S, Lau RW, et al (1996) The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz–20 GHz. Phys Med Biol 41(11):2251–2269

    Article  Google Scholar 

  8. Hyttinen J (1994) Development of regional aimed ECG leads especially for myocardial ischemia diagnosis. Ragnar Granit Institute. Tampere, Tampere University of Technology, p162

  9. Hyttinen JAK, Malmivuo JA, Walker SJ (1993) Lead field of ECG leads calculated by a computer thorax model-an application of reciprocity. In: Proceedings of the Computers in cardiology, 5–8 September 1993, pp 241–244

  10. Johnson CR (1997) Computational and numerical methods for bioelectric field problems. Crit Rev Biomed Eng 25(1):1–81

    MATH  Google Scholar 

  11. Jorgenson DB, Haynor DR, et al (1995) Computational studies of transthoracic and transvenous defibrillation in a detailed 3-D human thorax model. IEEE Trans Biomed Eng 42(2):172–184

    Article  Google Scholar 

  12. Kauppinen P, Hyttinen J, et al (1998) Detailed model of the thorax as a volume conductor based on the visible human man data. J Med Eng Technol 22(3):126–133

    Article  Google Scholar 

  13. Kauppinen P, Hyttinen J, et al (1999) A software implementation for detailed volume conductor modelling in electrophysiology using finite difference method. Comput Methods Programs Biomed 58(2):191–203

    Article  Google Scholar 

  14. Klepfer RN, Johnson CR, et al (1997) The effects of inhomogeneities and anisotropies on electrocardiographic fields: a 3-D finite-element study. IEEE Trans Biomed Eng 44(8):706–719

    Article  Google Scholar 

  15. Krasteva VT, Papazov SP (2002) Estimation of current density distribution under electrodes for external defibrillation. Biomed Eng Online 1(1):7

    Article  Google Scholar 

  16. Laarne P, Eskola H, et al (1995) Validation of a detailed computer model for the electric fields in the brain. J Med Eng Technol 19(2–3):84–87

    Google Scholar 

  17. Laarne P, Hyttinen J, et al (2000) Accuracy of two dipolar inverse algorithms applying reciprocity for forward calculation. Comput Biomed Res 33(3):172–185

    Article  Google Scholar 

  18. Malmivuo J, Plonsey R (1995) Bioelectromagnetism: principles and applications of bioelectric and biomagnetic fields. Oxford University Press, New York

    Google Scholar 

  19. Panescu D, Webster JG, et al (1994) Modeling current density distributions during transcutaneous cardiac pacing. IEEE Trans Biomed Eng 41(6):549–555

    Article  Google Scholar 

  20. Papazov S, Kostov Z, et al (2002) Electrical current distribution under transthoracic defibrillation and pacing electrodes. J Med Eng Technol 26(1):22–27

    Article  Google Scholar 

  21. Riistama J, Väisänen J, et al (2005) Introducing a wireless, passive and implantable device to measure ECG. In: IFMBE proceedings of the third European Medical and Biological Engineering Conference, IFMBE, Prague

  22. Sachse FB (2004) Computational cardiology: modeling of anatomy electrophysiology, and mechanics. Springer, Berlin

    MATH  Google Scholar 

  23. Song Z, Jenkins J, et al (2004) The feasibility of ST-segment monitoring with a subcutaneous device. J Electrocardiol 37(Suppl 1):174–179

    Article  Google Scholar 

  24. Takano N (2002) Reduction of ECG leads and equivalent sources using orthogonalization and clustering techniques. Ragnar Granit Institute. Tampere, Tampere University of Technology, p302

  25. Vehkaoja A, Lekkala J (2004) Wearable wireless biopotential measurement device. In: Proceedings of the 26th annual international conference of EMBC 2004, vol 3, pp 2177–2179. Engineering in Medicine and Biology Society

  26. Vaisanen J, Hyttinen J, Puurtinen M, Kauppinen P, Malmivuo J (2004) Prediction of implantable ECG lead systems by using thorax models. In: Proceedings of the 26th annual international conference of EMBC 2004, vol 2, pp 809–812. Engineering in Medicine and Biology Society

Download references

Acknowledgements

We would like to thank PhD Noriyuki Takano for providing the finite different method software. We would also like to thank MSc Tuukka Arola for providing the visualization tools. This work has been part of WIRELESS-project (5205437) funded by the Academy of Finland. The work has been supported also by the grants from the Finnish Cultural Foundation and the Ragnar Granit Foundation.

Author information

Authors and Affiliations

  1. Ragnar Granit Institute, Tampere University of Technology, P.O. Box 692, 33101, Tampere, Finland

    Juho Väisänen, Jari Hyttinen & Jaakko Malmivuo

Authors
  1. Juho Väisänen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jari Hyttinen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaakko Malmivuo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Juho Väisänen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Väisänen, J., Hyttinen, J. & Malmivuo, J. Finite difference and lead field methods in designing implantable ECG monitor. Med Bio Eng Comput 44, 857–864 (2006). https://doi.org/10.1007/s11517-006-0092-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-006-0092-7

Keywords

Search

Navigation