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Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 528781, 12 pages
Research Article

An Automated Optimal Engagement and Attention Detection System Using Electrocardiogram

Department of Computer Science, School of Engineering, Virginia Commonwealth University, 401 West Main Street, P.O. Box 843019, Richmond, VA 23284-3019, USA

Received 1 May 2012; Accepted 18 June 2012

Academic Editor: Alberto Guillén

Copyright © 2012 Ashwin Belle 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.

  • Ning-Han Liu, Cheng-Yu Chiang, and Hsuan-Chin Chu, “Recognizing the Degree of Human Attention Using EEG Signals from Mobile Sensors,” Sensors, vol. 13, no. 8, pp. 10273–10286, 2013. View at Publisher · View at Google Scholar
  • Chih-Ming Chen, and Sheng-Hui Huang, “Web-based reading annotation system with an attention-based self-regulated learning mechanism for promoting reading performance,” British Journal of Educational Technology, 2013. View at Publisher · View at Google Scholar
  • Yerim Choi, Namyeon Kwon, Sungjun Lee, Yongwook Shin, Chuh Yeop Ryo, Jonghun Park, and Dongmin Shin, “Hypovigilance Detection for UCAV Operators Based on a Hidden Markov Model,” Computational and Mathematical Methods in Medicine, vol. 2014, pp. 1–13, 2014. View at Publisher · View at Google Scholar
  • Tian Liu, Pan Lin, Yanni Chen, and Jue Wang, “Electroencephalogram synchronization analysis for attention deficit hyperactivity disorder children,” Bio-Medical Materials and Engineering, vol. 24, no. 1, pp. 1035–1039, 2014. View at Publisher · View at Google Scholar
  • Qichang He, Wei Li, Xiumin Fan, and Zhimin Fei, “Driver fatigue evaluation model with integration of multi-indicators based on dynamic Bayesian network,” Iet Intelligent Transport Systems, vol. 9, no. 5, pp. 547–554, 2015. View at Publisher · View at Google Scholar