{"title":"Kalman Filter Based Adaptive Reduction of Motion Artifact from Photoplethysmographic Signal","authors":"S. Seyedtabaii, L. Seyedtabaii","volume":13,"journal":"International Journal of Electronics and Communication Engineering","pagesStart":13,"pagesEnd":17,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/7359","abstract":"Artifact free photoplethysmographic (PPG) signals are\r\nnecessary for non-invasive estimation of oxygen saturation (SpO2) in\r\narterial blood. Movement of a patient corrupts the PPGs with motion\r\nartifacts, resulting in large errors in the computation of Sp02. This\r\npaper presents a study on using Kalman Filter in an innovative way\r\nby modeling both the Artillery Blood Pressure (ABP) and the\r\nunwanted signal, additive motion artifact, to reduce motion artifacts\r\nfrom corrupted PPG signals. Simulation results show acceptable\r\nperformance regarding LMS and variable step LMS, thus\r\nestablishing the efficacy of the proposed method.","references":"[1] K. W. Chan and Y. T. Zhang, \"Adaptive Reduction of Motion Artifact\r\nfrom Photoplethysmographic Recordings using a Variable Step Size\r\nLMS Filter,\" Sensors, 2002. Proceedings of IEEE, Volume: 2, pp. 1343-\r\n1346.\r\n[2] P. D. Larsen, M. H. Mohana Thirchelvarn, and Duncan C. Galletly,\r\n\"Spectral analysis of AC and DC components of the pulse\r\nphotoplethysmogrphy at rest and during induction of anesthesia,\"\r\nInternational Journal of Clinical Monitoring and Computing, 1997, 14,\r\npp.89-95.\r\n[3] B. S. Kim and S. K. Yoo, \"Motion artifact reduction in\r\nphotoplethysmography using independent component analysis,\" IEEE\r\nTransactions on Biomedical Engineering, Volume 53, Issue 3, March\r\n2006 Page(s): 566 - 568.\r\n[4] M. J. Hayes and P. R. Smith, \"Artifact Reduction in\r\nPhotoplethysmography, \"Applied Optics, Vol. 37, Issue 31, pp. 7437-\r\n7446\r\n[5] Y Yan, C Poon and f Y Zhang, \"Reduction of motion artifact in pulse\r\noximetry by smoothed pseudo Wigner-Ville distribution,\" Journal of\r\nNeuroEngineering and Rehabilitation 2005, 2:3\r\n[6] J. B. Evans and B. Liu, \"Variable step size methods for the LMS\r\nadaptive algorithms,\" IEEE Int. Symp. Circuits. Syst. Proc, 1987,\r\npp.422-425.\r\n[7] E. W. Harris and C.D.M.a.B.F.A., \"A variable step (VS) adaptive filter\r\nalgorithm,\" IEEE Transactions on Biomedical Engineering, 1986, Vol.\r\n34, pp.309-316.\r\n[8] R. Mukkamala, AT Reisner, HM Hojman, RG Mark, and RJ Cohen,\r\n\"Continuous cardiac output monitoring by peripheral blood pressure\r\nwaveform analysis,\" IEEE Trans Biomed Eng, 53: 459-467, 2006.\r\n[9] Z Lu and R Mukkamala, \"Continuous cardiac output monitoring in\r\nhumans by invasive and noninvasive peripheral blood pressure\r\nwaveform analysis,\" J Appl Physiol 101: 598-608, 2006;\r\n[10] N Townsend, M. Term, \"Pulse Oximetry,\" Medical Electronics, 2001,\r\npp.35-45\r\n[11] Bernard Widrow, J.M.M., Michael G. Larimore and C.Richard Johnson,\r\n\"Adaptive noise canceling: Principles and applications,\" Proceedings of\r\nIEEE, Dec. 1975, Vo163, pp.1692-1716.\r\n[12] S. Haykin, Adaptive Filter Theory. Fourth Edition. Prentice-Hall, Inc.,\r\nEnglewood Cliffs, NJ, 2002.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 13, 2008"}