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The Scientific World Journal
Volume 2012, Article ID 353081, 7 pages
http://dx.doi.org/10.1100/2012/353081
Research Article

A Data-Driven Noise Reduction Method and Its Application for the Enhancement of Stress Wave Signals

School of Information Engineering, Zhejiang A & F University, Zhejiang, Lin'an 311300, China

Received 15 September 2012; Accepted 15 October 2012

Academic Editors: W.-J. Hwang, M. Riera-Guasp, and V. Valimaki

Copyright © 2012 Hai-Lin Feng 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.

Citations to this Article [5 citations]

The following is the list of published articles that have cited the current article.

  • Ashish Verma, Pratik, and Gayadhar Pradhan, “Electrocardiogram denoising using Wavelet decomposition and EMD domain filtering,” 2016 IEEE Region 10 Conference (TENCON), pp. 2185–2189, . View at Publisher · View at Google Scholar
  • David Camarena-Martinez, Martin Valtierra-Rodriguez, Arturo Garcia-Perez, Roque Alfredo Osornio-Rios, and Rene de Jesus Romero-Troncoso, “Empirical Mode Decomposition and Neural Networks on FPGA for Fault Diagnosis in Induction Motors,” The Scientific World Journal, vol. 2014, pp. 1–17, 2014. View at Publisher · View at Google Scholar
  • Shamim Samadi, and Mohammad B. Shamsollahi, “ECG noise reduction using empirical mode decomposition based on combination of instantaneous half period and soft-thresholding,” Middle East Conference on Biomedical Engineering, MECBME, pp. 244–248, 2014. View at Publisher · View at Google Scholar
  • Cédric Damour, Michel Benne, Brigitte Grondin-Perez, Miloud Bessafi, Daniel Hissel, and Jean-Pierre Chabriat, “Polymer electrolyte membrane fuel cell fault diagnosis based on empirical mode decomposition,” Journal of Power Sources, vol. 299, pp. 596–603, 2015. View at Publisher · View at Google Scholar
  • Mohammod Abdul Motin, Chandan Kumar Karmakar, and Marimuthu Palaniswami, “Ensemble Empirical Mode Decomposition With Principal Component Analysis: A Novel Approach for Extracting Respiratory Rate and Heart Rate From Photoplethysmographic Signal,” IEEE Journal of Biomedical and Health Informatics, vol. 22, no. 3, pp. 766–774, 2018. View at Publisher · View at Google Scholar