Kalman Filter Based Adaptive Reduction of Motion Artifact from Photoplethysmographic Signal
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Kalman Filter Based Adaptive Reduction of Motion Artifact from Photoplethysmographic Signal

Authors: S. Seyedtabaii, L. Seyedtabaii

Abstract:

Artifact free photoplethysmographic (PPG) signals are necessary for non-invasive estimation of oxygen saturation (SpO2) in arterial blood. Movement of a patient corrupts the PPGs with motion artifacts, resulting in large errors in the computation of Sp02. This paper presents a study on using Kalman Filter in an innovative way by modeling both the Artillery Blood Pressure (ABP) and the unwanted signal, additive motion artifact, to reduce motion artifacts from corrupted PPG signals. Simulation results show acceptable performance regarding LMS and variable step LMS, thus establishing the efficacy of the proposed method.

Keywords: Kalman filter, Motion artifact, PPG, Photoplethysmography.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1333656

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References:


[1] K. W. Chan and Y. T. Zhang, "Adaptive Reduction of Motion Artifact from Photoplethysmographic Recordings using a Variable Step Size LMS Filter," Sensors, 2002. Proceedings of IEEE, Volume: 2, pp. 1343- 1346.
[2] P. D. Larsen, M. H. Mohana Thirchelvarn, and Duncan C. Galletly, "Spectral analysis of AC and DC components of the pulse photoplethysmogrphy at rest and during induction of anesthesia," International Journal of Clinical Monitoring and Computing, 1997, 14, pp.89-95.
[3] B. S. Kim and S. K. Yoo, "Motion artifact reduction in photoplethysmography using independent component analysis," IEEE Transactions on Biomedical Engineering, Volume 53, Issue 3, March 2006 Page(s): 566 - 568.
[4] M. J. Hayes and P. R. Smith, "Artifact Reduction in Photoplethysmography, "Applied Optics, Vol. 37, Issue 31, pp. 7437- 7446
[5] Y Yan, C Poon and f Y Zhang, "Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution," Journal of NeuroEngineering and Rehabilitation 2005, 2:3
[6] J. B. Evans and B. Liu, "Variable step size methods for the LMS adaptive algorithms," IEEE Int. Symp. Circuits. Syst. Proc, 1987, pp.422-425.
[7] E. W. Harris and C.D.M.a.B.F.A., "A variable step (VS) adaptive filter algorithm," IEEE Transactions on Biomedical Engineering, 1986, Vol. 34, pp.309-316.
[8] R. Mukkamala, AT Reisner, HM Hojman, RG Mark, and RJ Cohen, "Continuous cardiac output monitoring by peripheral blood pressure waveform analysis," IEEE Trans Biomed Eng, 53: 459-467, 2006.
[9] Z Lu and R Mukkamala, "Continuous cardiac output monitoring in humans by invasive and noninvasive peripheral blood pressure waveform analysis," J Appl Physiol 101: 598-608, 2006;
[10] N Townsend, M. Term, "Pulse Oximetry," Medical Electronics, 2001, pp.35-45
[11] Bernard Widrow, J.M.M., Michael G. Larimore and C.Richard Johnson, "Adaptive noise canceling: Principles and applications," Proceedings of IEEE, Dec. 1975, Vo163, pp.1692-1716.
[12] S. Haykin, Adaptive Filter Theory. Fourth Edition. Prentice-Hall, Inc., Englewood Cliffs, NJ, 2002.