Two-stage approach for detection and reduction of motion artifacts in photoplethysmographic data

IEEE Transactions on Biomedical Engineering

Volumn 57, Issue 8, 2010, Pages 1867-1876

  Krishnan, Rajet ^a   Natarajan, Balasubramaniam ^b   Warren, Steve ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

^b Kansas State University   (United States)

Author keywords

Higher order statistics (HOS); independent component analysis (ICA); magnitude based frequency domain ICA (FD ICA); motion artifact; motion detection unit (MDU); photoplethysmogram (PPG)

Indexed keywords

DATA PROCESSING; DATA REDUCTION; FINITE DIFFERENCE METHOD; FOURIER ANALYSIS; FOURIER SERIES; FREQUENCY DOMAIN ANALYSIS; FREQUENCY ESTIMATION; HARMONIC ANALYSIS; HEMODYNAMICS; MOBILE TELECOMMUNICATION SYSTEMS; NONINVASIVE MEDICAL PROCEDURES; OPTICAL VARIABLES MEASUREMENT; OXIMETERS; REPAIR; SENSOR DATA FUSION; SENSORS; SIGNAL ANALYSIS; SIGNAL DETECTION; SIGNAL PROCESSING; SIGNAL RECONSTRUCTION;

FREQUENCY DOMAINS; HIGHER ORDER STATISTICS; HIGHER ORDER STATISTICS (HOS); MOTION ARTIFACT; MOTION DETECTION; PHOTOPLETHYSMOGRAM;

INDEPENDENT COMPONENT ANALYSIS;

ARTICLE; ARTIFACT; ARTIFACT REDUCTION; AUTOMATION; CORRELATION COEFFICIENT; ELECTRON; INDEPENDENT COMPONENT ANALYSIS; INFORMATION PROCESSING; MEDICAL DECISION MAKING; MOTION; PLETHYSMOGRAPHY; PULSE WAVE; SENSOR; STATISTICS; UNITED STATES; ADULT; ALGORITHM; FEMALE; FOREARM; FOURIER ANALYSIS; HUMAN; MALE; MOVEMENT (PHYSIOLOGY); NORMAL DISTRIBUTION; PHOTOELECTRIC PLETHYSMOGRAPHY; PHYSIOLOGY; PROCEDURES; RECEIVER OPERATING CHARACTERISTIC; SIGNAL PROCESSING; STATISTICAL ANALYSIS;

ADULT; ALGORITHMS; ARTIFACTS; DATA INTERPRETATION, STATISTICAL; FEMALE; FOREARM; FOURIER ANALYSIS; HUMANS; MALE; MOVEMENT; NORMAL DISTRIBUTION; PHOTOPLETHYSMOGRAPHY; ROC CURVE; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 77954652184     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2009.2039568     Document Type: Article

References (27)

1. R. Krishnan, B. Natarajan, and S.Warren, "Analysis and detection of motion artifacts in photoplethysmographic data using higher order statistics," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. (ICASSP 2008), Las Vegas, Nevada, Apr. 2008, pp. 613-616.
2. R. Krishnan, B. Natarajan, and S. Warren, "Motion artifact reduction in photoplethysmography using magnitude-based frequency domain independent component analysis," in Proc. 17th Int. Conf. Comput. Commun. Network, St. Thomas, Virgin Islands, Aug. 2008, pp. 1-5.
3. Z.Chair and P.Varshney, "Optimal data fusion in multiple sensor detection systems," IEEE Trans. Aerosp. Electron. Syst., AES, vol.1, no.1, pp. 98-101, Jan. 1986.
4. C. C. Lee and J. J. Chao, "Optimum local decision space partitioning for distributed detection," IEEE Trans. Aerosp. Electron. Syst., AES, vol.25, no.7, pp. 536-544, Jul. 1989.
5. S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Cote, "Processing of pulse oximeter data using discrete wavelet analysis," IEEE Trans. Biomed. Eng., vol.52, no.7, pp. 1350-1352, Jul. 2005.
6. J. M. Graybeal and M. T. Petterson, "Adaptive filtering and alternative calculations revolutionizes pulse oximetry sensitivity and specificity during motion and low perfusion," in Proc. 26th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., San Fransisco, Sep. 2004, vol.2, pp. 5363-5366.
7. J. Y. A. Foo, "Comparison of wavelet transformation and adaptive filtering in restoring artifact-induced time-related measurement," Biomed. Signal Process. Control, vol.1, no.1, pp. 93-98, 2006.
8. J. E. Scharf, S. Athan, and D. Cain, "Pulse oximetry through spectral analysis," in Proc. 12th Southern Biomed. Eng. Conf., New Orleans, LA, Apr. 1993, pp. 227-229.
9. B. S. Kim and S. K. Yoo, "Motion artifact reduction in photoplethysmography using independent component analysis," IEEE Trans. Biomed. Eng., vol.53, no.3, pp. 566-568, Mar. 2006.
10. J. Weng, Z. Ye, and J. Weng, "An improved pre-processing approach for photoplethysmographic signal," in Proc. 27th Annu. Int. Conf. Eng. Med. Biol. Soc., Sep. 2005, pp. 41-44.
11. M. K. Diab, E. Kiani-Azarbayjany, I. M. Elfadel, R. J. McCarthy, W. M. Weber, and R. A. Smith, "Signal processing apparatus," U.S. Patent 721 598 4, May 2007.
12. N. Mammone and F.C Morabito, "Independent component analysis and high-order statistics for automatic artifact rejection," in Proc. IEEE Int. Joint Conf. Neural Netw. (IJCNN 2005), Montreal, Quebec, Aug., vol.4, pp. 2447-2452.
13. J. Yao and S. Warren, "A short study to assess the potential of independent component analysis for motion artifact separation in wearable pulse oximeter signals," in Proc. 27th Annu. Int. Conf. Eng. Med. Biol. Soc., 2005, pp. 3585-3588.
14. D. Thompson and S. Warren, "A small, high-fidelity reflectance pulse oximeter," presented at the Annual Conf. Exposition, American Society of Engineering Education, Honolulu, Hawaii, Jun. 24-27, 2007.
15. B. Pilgram, P. Castiglioni, G. Parati, and M. Di Rienzo, "Dynamic detection of rhythmic oscillations in heart-rate tracings: A state-space approach based on fourth-order cumulants," Biol. Cyberern., vol.76, pp. 299-309, 1997.
16. J. M. Mendel, "Tutorial on higher-order statistics (spectra) in signal processing and system theory: Theoretical results and some applications," Proc. IEEE, vol.79, no.1, pp. 278-305, Jan. 1991.
17. C. L. Nikias and A. P. Petropulu, Higher-Order Spectra Analysis: A Nonlinear Signal Processing Framework. Englewood Clifs, NJ: Prentice-Hall, 1993.
18. A. Swami, J. M. Mendel, andC. L.Nikias, Higher-Order Spectral Analysis Toolbox User's Guide, R12 for Use With MATLABR . United Signals and Systems, Inc., 2000.
19. C. L. Nikias and M. R. Raghuveer, "Bispectrum estimation: A digital signal processing framework," Proc. IEEE, vol.75, no.7, pp. 867-891, Jul. 1987.
20. A. Mansour and C. Jutten, "What should we say about the kurtosis?" IEEE Signal Process. Lett., vol.6, no.12, pp. 321-322, Dec. 1999.
21. R. F. Dwyer, "Use of the Kurtosis statistic in the frequency domain as an aid in detecting random signals," IEEE J. Ocean. Eng., vol.9, no.2, pp. 85-92, Apr. 1984.
22. H. Poor, An Introduction to Signal Detection and Estimation, 2nd ed. New York: Springer-Verlag, 1994.
23. J. Muthuswamy, D. L. Sherman, and N. V. Thakor, "Higher-order spectral analysis of burst patterns in EEG," IEEE Trans. Biomed. Eng., vol.46, no.1, pp. 92-99, Jan. 1999.
24. P. Smaragdis, "Blind separation of convolved mixtures in the frequency domain," presented at the Int. Workshop Independence and Artificial on Neural Networks, University of La Laguna, Tenerife, Spain, Feb. 1998.
25. A. Hyvrinen, "Fast and robust fixed-point algorithms for independent component analysis," IEEE Trans. Neural Netw., vol.10, no.3, pp. 626-634, Mar. 1999.
26. H. M. Park, Y. Jung, T. W. Lee, and S. Y. Lee, "On subband-based blind signal separation for noisy speech recognition," Electron. Lett., vol.35, pp. 2011-2012, 1999.
27. E. Bingham and A. Hyvrinen, "A fast fixed-point algorithm for independent component analysis of complex-valued signals," Int. J. Neural Syst., vol.10, pp. 1-8, 2000.