The Effect of White Noise and False Peak Detection on HRV Analysis

G. Manis, A. Alexandridi, S. Nikolopoulos, K. Davos

Abstract

Heart rate variability (HRV) is an established measure for cardiac health. Its use is widespread and many methods have been developed for its analysis. Little emphasis, however, has been given to the specific influence of noise from the electrocardiogram (ECG) on the heart rate (HR) series. There are explicit factors of noise that have been extensively studied on the ECG and much work has been published on their limitation or elimination. Despite all these solutions, however, often noise does end up in the ECG and is inevitably included in the derived HR series. It is of interest to investigate how this influences subsequent HRV analysis. We propose that the noise into the resulting HR series: Shifted R-peak (white noise) and false peaks. In this paper, we demonstrate how these two scenarios affect the outcome of the HRV analysis.

References

  1. 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 (1996) 93:1043-1065
  2. Teich MC, Lowen SB, Jost BM, Vibe-Rheymer K, Heneghan C.: Heart-Rate Variability: Measures and Models. Nonlinear Biomed Signal Processing, Vol. II, Dynamic Analysis and Modeling. M. Akay, IEEE Press, New York (2001) 159-213
  3. Daskalov, I.K, Dotsinsky I.A., Christov I.I.: Developments in ECG Acquisition, Preprocessing, Parameter Measurement, and Recording. In IEEE Eng Med Biol, (1998) 17(2):50-58.
  4. Hilton M.F., Beattie J.M., Chappell M.J., Bates R.A.: Heart rate variability: measurement error or chaos? Computers in Cardiology (1998) 24:125-128
  5. Signorini MG, Marchetti F, Cerutti S.: Applying nonlinear noise reduction in the analysis of heart rate variability. In IEEE Eng Med Biol Mag. (2001) 20(2):59-68
  6. Friesen, G.M., Jannett, T.C., Jadallah, M.A., Yates, S.L., Quint, S. R. and Nagle, H.T., 1990. A comparison of the noise sensitivity of nine QRS detection algorithms.In IEEE Trans Biomed. Eng, 1990;37:85-98.
  7. Adli, Yamamoto, Y.: Impedance balancing analysis for power-line interference elimination in ECG signal. IMTC/98. Conference Proceedings (1998) 1:235 - 238
  8. Hamilton, P.S.: A comparison of adaptive and nonadaptive filters for reduction of power line interference in the ECG. IEEE Trans Biomed Eng (1996) 43(1):105 - 109
  9. Ziarani, A.K., Konrad, A.: A nonlinear adaptive method of elimination of power line interference in ECG signals. IEEE Trans Biomed Eng (2002) 49(6):540 - 547
  10. Hamilton, P.S., Curley, M.G., Aimi, R.M., Sae-Hau, C.: Comparison of methods for adaptive removal of motion artefact. In Comp in Cardiol (2000) 383 - 386
  11. Tong, D.A., Bartels, K.A., Honeyager, K.S.: Adaptive reduction of motion artifact in the electrocardiogram. Engineering in Medicine and Biology, 2002. EMBS/BMES Conference (2002) 2:1403 - 1404.
  12. Hamilton, P.S., Curley, M.G.: Adaptive removal of motion artifact [ECG recordings] Engineering in Medicine and Biology society, Proceedings of the 19th Annual International Conference of the IEEE (1997) 1:297 - 299
  13. Sun, P., Wu, Q.H., Weindling, A.M., Finkelstein, A., Ibrahim, K.: An improved morphological approach to background normalization of ECG signals. IEEE Trans Biomed Eng (2003) 50(1):117 - 121
  14. Benitez, I., Lu, C.-C.: Portable real-time body surface Laplacian ECG mapping. BMES/EMBS Conference (1999) 1:301
  15. Pandit, S.V.: ECG baseline drift removal through STFT. Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE (1996) 4:1405 - 1406
  16. Cuiwei L., Chongxun Z., Changfeng T.: Detection of ECG characteristic points using wavelet transforms. IEEE Trans Biomed Eng (1995) 42(1):21 - 28
  17. Manis G., Nikolopoulos S., Alexandridi A.: Prediction Techniques and HRV Analysis. MEDICON (2004).
  18. Porta A, Baselli G, Guzzetti S, Pagani M, Malliani A, Cerutti S.: Prediction of short cardiovascular variability signals based on conditional distribution. IEEE Trans Biomed Eng. (2000) 47(12):1555-64.
Download


Paper Citation


in Harvard Style

Manis G., Alexandridi A., Nikolopoulos S. and Davos K. (2005). The Effect of White Noise and False Peak Detection on HRV Analysis . In Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005) ISBN 972-8865-35-X, pages 161-166. DOI: 10.5220/0001195301610166


in Bibtex Style

@conference{bpc05,
author={G. Manis and A. Alexandridi and S. Nikolopoulos and K. Davos},
title={The Effect of White Noise and False Peak Detection on HRV Analysis},
booktitle={Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005)},
year={2005},
pages={161-166},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001195301610166},
isbn={972-8865-35-X},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2005)
TI - The Effect of White Noise and False Peak Detection on HRV Analysis
SN - 972-8865-35-X
AU - Manis G.
AU - Alexandridi A.
AU - Nikolopoulos S.
AU - Davos K.
PY - 2005
SP - 161
EP - 166
DO - 10.5220/0001195301610166