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Zhang, J., Zou, J., Wang, M., et al. (2013) Automatic Detection of Interictal Epileptiform Discharges Based on Time-Series Sequence Merging Method. Neurocomputing, 110, 35-43. http://dx.doi.org/10.1016/j.neucom.2012.11.017

has been cited by the following article:

• TITLE: The Application of Visual Organization Principle in the Detection of Sleep Spindles

  AUTHORS: Xuemei Jin, Junzhong Zou, Jian Zhang

  KEYWORDS: Sleep Spindles, Principle of Visual Organization, Time-Domain Detection

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.10 No.5B, May 10, 2017

  ABSTRACT: In order to detect the sleep spindles simply and efficiently, a novel time-domain approach to detect sleep spindles based on the principles of visual organization is proposed. The code idea of the visual organization is to organize the primary visual elements according to some rules of organization, and to form a more meaningful object of visual processing, as the input of next process. After the collected EEG is processed with the merging algorithm based on the principle of visual organization, it can extract the time-domain feature frequency and duration time better. Use these features with a simple algorithm to detect spindles achieving sensitivity of 92.5% and specificity of 98.1%, which verifies the validity of this method to detect the sleep spindles.