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Computational and Mathematical Methods in Medicine
Volume 2018, Article ID 6812404, 8 pages
https://doi.org/10.1155/2018/6812404
Research Article

Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography

1Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne NE2 4HH, UK
2Northern Medical Physics and Clinical Engineering, Newcastle upon Tyne NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK

Correspondence should be addressed to John Allen; ku.shn.htun@nella.nhoj

Received 4 August 2017; Accepted 31 December 2017; Published 29 January 2018

Academic Editor: Chung-Min Liao

Copyright © 2018 William Waugh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. V. J. Challoner, “Photoelectric plethysmography for estimating cutaneous blood flow,” in Non-Invasive Physiological Measurements, P. Rolfe, Ed., pp. 1125–1151, Academic, London, UK, 1979. View at Google Scholar
  2. W. M. Nichols and M. F. O’Rourke, McDonald’s Blood Flow in Arteries, Arnold, London, UK, 3rd edition, 1990.
  3. I. B. Wilkinson, J. R. Cockcroft, and D. J. Webb, “Pulse wave analysis and arterial stiffness,” Journal of Cardiovascular Pharmacology, vol. 3, pp. S33–S37, 1998. View at Google Scholar
  4. A. A. R. Kamal, J. B. Harness, G. Irving, and A. J. Mearns, “Skin photoplethysmography - a review,” Computer Methods and Programs in Biomedicine, vol. 28, no. 4, pp. 257–269, 1989. View at Publisher · View at Google Scholar · View at Scopus
  5. J. Allen, “Photoplethysmography and its application in clinical physiological measurement,” Physiological Measurement, vol. 28, no. 3, pp. R1–R39, 2007. View at Publisher · View at Google Scholar · View at Scopus
  6. S. Wilkes, G. Stansby, A. Sims, S. Haining, and J. Allen, “Peripheral arterial disease: diagnostic challenges and how photoplethysmography may help,” British Journal of General Practice, vol. 65, no. 635, pp. 323-324, 2015. View at Publisher · View at Google Scholar · View at Scopus
  7. K. T. Sweeney, T. E. Ward, and S. F. McLoone, “Artifact removal in physiological signals-practices and possibilities,” IEEE Transactions on Information Technology in Biomedicine, vol. 16, no. 3, pp. 488–500, 2012. View at Publisher · View at Google Scholar · View at Scopus
  8. T. R. H. Cutmore and D. A. James, “Identifying and reducing noise in psychophysiological recordings,” International Journal of Psychophysiology, vol. 32, no. 2, pp. 129–150, 1999. View at Publisher · View at Google Scholar · View at Scopus
  9. M. Mamun, M. Al-Kadi, and M. Marufuzzaman, “Effectiveness of wavelet denoising on electroencephalogram signals,” Journal of Applied Research and Technology, vol. 11, no. 1, pp. 156–160, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. C. Orphanidou, T. Bonnici, P. Charlton, D. Clifton, D. Vallance, and L. Tarassenko, “Signal-quality indices for the electrocardiogram and photoplethysmogram: Derivation and applications to wireless monitoring,” IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 3, pp. 832–838, 2015. View at Publisher · View at Google Scholar · View at Scopus
  11. J. A. Sukor, S. J. Redmond, and N. H. Lovell, “Signal quality measures for pulse oximetry through waveform morphology analysis,” Physiological Measurement, vol. 32, no. 3, pp. 369–384, 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. I. Silva, J. Lee, and R. G. Mark, “Signal quality estimation with multichannel adaptive filtering in intensive care settings,” IEEE Transactions on Biomedical Engineering, vol. 59, no. 9, pp. 2476–2485, 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. M. Elgendi, “Optimal Signal Quality Index for Photoplethysmogram Signals,” Bioengineering, vol. 3, no. 4, p. 21, 2016. View at Publisher · View at Google Scholar
  14. V. Estivill-Castro, “Why so many clustering algorithms: a position paper,” ACM SIGKDD Explorations Newsletter, vol. 4, no. 1, pp. 65–75, 2002. View at Publisher · View at Google Scholar
  15. J. Allen, K. Overbeck, A. F. Nath, A. Murray, and G. Stansby, “A prospective comparison of bilateral photoplethysmography versus the ankle-brachial pressure index for detecting and quantifying lower limb peripheral arterial disease,” Journal of Vascular Surgery, vol. 47, no. 4, pp. 794–802, 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. http://www.omg.org/spec/BPMN/2.0.
  17. R. G. Lyons, Understanding Digital Signal Processing, Pearson, 2004.
  18. S. W. Smith, Digital Signal Processing: A Practical Guide for Engineers and Scientists, Newnes, 2002.
  19. J. Pan and W. J. Tompkins, “A real-time QRS detection algorithm,” IEEE Transactions on Biomedical Engineering, vol. 32, no. 3, pp. 230–236, 1985. View at Google Scholar · View at Scopus