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Computational and Mathematical Methods in Medicine
Volume 2017, Article ID 7949507, 9 pages
https://doi.org/10.1155/2017/7949507
Research Article

Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine

Lili Chen1,2 and Yaru Hao1,2

1School of Mechatronics & Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China
2School of Chongqing Key Laboratory of Urban Rail Transit Vehicle System Integration and Control, Chongqing Jiaotong University, Chongqing 400074, China

Correspondence should be addressed to Lili Chen; nc.ude.utjqc@225ililc

Received 4 August 2016; Revised 7 November 2016; Accepted 26 January 2017; Published 19 February 2017

Academic Editor: Hiro Yoshida

Copyright © 2017 Lili Chen and Yaru Hao. 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 [4 citations]

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

  • Nafissa Sadi-Ahmed, Baya Kacha, Hamza Taleb, and Malika Kedir-Talha, “Relevant Features Selection for Automatic Prediction of Preterm Deliveries from Pregnancy ElectroHysterograhic (EHG) records,” Journal of Medical Systems, vol. 41, no. 12, 2017. View at Publisher · View at Google Scholar
  • Shui-Hua Wang, Khan Muhammad, Preetha Phillips, Zhengchao Dong, and Yu-Dong Zhang, “Ductal carcinoma in situ detection in breast thermography by extreme learning machine and combination of statistical measure and fractal dimension,” Journal of Ambient Intelligence and Humanized Computing, 2017. View at Publisher · View at Google Scholar
  • Franc Jager, Sonja Libenšek, and Ksenija Geršak, “Characterization and automatic classification of preterm and term uterine records,” Plos One, vol. 13, no. 8, pp. e0202125, 2018. View at Publisher · View at Google Scholar
  • Gustavo Pacheco-López, Lenin Pavón, Rodrigo Ayala-Yáñez, José Javier Reyes-Lagos, Juan Carlos Echeverría, María Teresa García-González, Claudia Ivette Ledesma-Ramírez, Jorge Escalante-Gaytán, Ramón González-Camarena, Miguel Ángel Peña-Castillo, and Enrique Becerril-Villanueva, “Associations of Immunological Markers and Anthropometric Measures with Linear and Nonlinear Electrohysterographic Parameters at Term Active Labor,” Advances in Neuroimmune Biology, vol. 7, no. 1, pp. 27–36, 2018. View at Publisher · View at Google Scholar