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The Scientific World Journal
Volume 2014, Article ID 295070, 11 pages
http://dx.doi.org/10.1155/2014/295070
Research Article

Detection of Burst Suppression Patterns in EEG Using Recurrence Rate

1Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
2State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
3Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing 100875, China
4Institute of Information and Science Engineering, Yanshan University, Qinhuangdao 066004, China
5Department of Anesthesia, Waikato Hospital, Hamilton, New Zealand

Received 21 January 2014; Accepted 20 February 2014; Published 17 April 2014

Academic Editors: H.-K. Lam, J. Li, G. Ouyang, and T. Stathaki

Copyright © 2014 Zhenhu Liang 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 [9 citations]

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

  • Alejandro Martin, Guillermina Guerrero-Mora, Guadalupe Dorantes-Mendez, Alfonso Alba, Martin O. Mendez, and Ioanna Chouvarda, “Non-linear analysis of EEG and HRV signals during sleep,” 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4174–4177, . View at Publisher · View at Google Scholar
  • Jingzhi An, Durga Jonnalagadda, Valdery Moura, Patrick L. Purdon, Emery N. Brown, and M. Brandon Westover, “Spatial variation in automated burst suppression detection in pharmacologically induced coma,” 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 7430–7433, . View at Publisher · View at Google Scholar
  • Fuwang Wang, and Hong Wang, “Study of Driving Fatigue Alleviation by Transcutaneous Acupoints Electrical Stimulations,” The Scientific World Journal, vol. 2014, pp. 1–8, 2014. View at Publisher · View at Google Scholar
  • Christos Papadelis, Seyedeh Fatemeh Salimi Ashkezari, Chiran Doshi, Sigride Thome, Phillip L. Pearl, Patricia Ellen Grant, Robert C. Tasker, and Tobias Loddenkemper, “Real-time multi-channel monitoring of burst-suppression using neural network technology during pediatric status epilepticus treatment,” Clinical Neurophysiology, 2016. View at Publisher · View at Google Scholar
  • Franz Fürbass, Johannes Herta, Johannes Koren, M. Brandon Westover, Manfred M. Hartmann, Andreas Gruber, Christoph Baumgartner, and Tilmann Kluge, “Monitoring burst suppression in critically ill patients: Multi-centric evaluation of a novel method,” Clinical Neurophysiology, 2016. View at Publisher · View at Google Scholar
  • Rajesh Sharma Sivasubramony, Vladimir Miskovic, Chun-An Chou, Miaolin Fan, Mohammad Samie Tootooni, and Prahalada K. Rao, “Acute stress detection using recurrence quantification analysis of electroencephalogram (EEG) signals,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9919, pp. 252–261, 2016. View at Publisher · View at Google Scholar
  • Parisa Mirzaei, and Ghasem Azemi, “A new NLEO based technique for the detection of burst–suppression patterns in multichannel neonatal EEG signals,” Analog Integrated Circuits and Signal Processing, vol. 92, no. 2, pp. 255–262, 2017. View at Publisher · View at Google Scholar
  • Parisa Mirzaei, Ghasem Azemi, Natia Japaridze, and Boualem Boashash, “Surrogate data test for nonlinearity of EEG signals: A newborn EEG burst suppression case study,” Digital Signal Processing, 2017. View at Publisher · View at Google Scholar
  • Fuwang Wang, Hong Wang, and Rongrong Fu, “Real-Time ECG-Based Detection of Fatigue Driving Using Sample Entropy,” Entropy, vol. 20, no. 3, pp. 196, 2018. View at Publisher · View at Google Scholar