Skip to main content
SpringerLink
Log in

Baseline Drift Filtering for an Arterial Pulse Signal

  • Medical and Biological Measurements
  • Published:
Measurement Techniques Aims and scope

Different baseline drift filtering methods are examined for an arterial pulse signal. A baseline drift correction method is proposed that is based on generating an adaptive filter reference signal using multiresolution wavelet transforms of the original biosignal, making it possible to achieve the least distortions in processing the signal compared with model signals free of distorting effects. The effectiveness of other methods for filtering the signal is studied when noise of different intensities is present.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. J. Allen, “Photoplethysmography and its application in clinical physiological measurement,” Physiol. Meas., 28, 1–39 (2007).

    Article  Google Scholar 

  2. J. G. Webster, Design of Pulse Oximeters. Med. Sci. Ser., Taylor and Francis (1997).

  3. L. I. Kalakutskii and E. S. Manelis, Clinical Monitoring Instrumentation and Methods [in Russian], Vyssh. Shkola, Moscow (2004).

    Google Scholar 

  4. R. M. Rangayyan, Biomedical Signal Analysis: A Case-Study Approach [Russian translation from English], Fizmatlit, Moscow (2007).

    Google Scholar 

  5. A. A. Fedotov and S. A. Akulov, Mathematical Modeling and Analysis of Uncertainties in Biomedical Signal Measurement Transducers [in Russian], Fizmatlit, Moscow (2013).

    Google Scholar 

  6. A. A. Fedotov, “Amplitude-time method for detection of characteristic points in a pulse wave signal,” Med. Tekhn., No. 6, 22–28 (2012).

  7. K. Q. Wang et al., “Pulse baseline wander removal using wavelet approximation,” IEEE Comp. Cardiol., 30, 605–608 (2003).

    Google Scholar 

  8. T. H. Fu et al., “Heart rate extraction from photoplethysmogram waveform using wavelet multi-resolution analysis,” J. Med. Biol. Eng., 28, No. 4, 229–232 (2008).

    Google Scholar 

  9. L. Xu et al., “Wavelet-based cascaded adaptive filter for removing baseline drift in pulse waveforms,” IEEE Trans. Biomed. Eng., 52, No. 11, 1973–1975 (2005).

    Article  ADS  Google Scholar 

  10. L. I. Kalakutskii and A. A. Fedotov, “Diagnosis of vascular endothelial dysfunction by pulse wave contour analysis,” Izv. YuFU. Tekhn. Nauki, No. 9, 93–98 (2009).

  11. X. Chen and R. Mukkamala, “Selective quantification of the cardiac sympathetic and parasympathetic nervous systems by multisignal analysis of cardiorespiratory variability,” J. Physiol., 294, 362–371 (2008).

    Google Scholar 

  12. A. A. Fedotov, “Selection of filtering parameters for an arterial pulse signal based on application of multi-resolution wavelet transforms,” Med. Tekhn., No. 3, 31–34 (2013).

  13. G. Strang and T. Nguyen, Wavelets and Filter Banks, Wellesley/Cambridge Press (1996).

Download references

Author information

Authors and Affiliations

  1. Korolev Samara State Aerospace University, Samara, Russia

    A. A. Fedotov

Authors
  1. A. A. Fedotov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. A. Fedotov.

Additional information

Translated from Izmeritel’naya Tekhnika, No. 1, pp. 59–62, January, 2014.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fedotov, A.A. Baseline Drift Filtering for an Arterial Pulse Signal. Meas Tech 57, 91–96 (2014). https://doi.org/10.1007/s11018-014-0413-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11018-014-0413-4

Keywords

Search

Navigation