Shujuan Geng

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Automatic seizure detection is significant for long-term monitoring of epilepsy, as well as for diagnostics and rehabilitation, and can decrease the duration of work required when inspecting the EEG signals. In this study we propose a novel method for feature extraction and pattern recognition of ictal EEG, based upon empirical mode decomposition (EMD) and(More)
DNA methylation has long been considered to play important roles in the regulation of plant response to multiple environmental stresses. As it is with saline soils, alkaline soils are important agricultural contaminants that have complex effects on plant metabolism and, in particular, on root physiology. However, there are no reports on epigenetic responses(More)
In this work, we evaluated the differences between epileptic electroencephalogram (EEG) and interictal EEG by computing some non-linear features. Correlation dimension (CD) and Hurst exponent (H) were calculated for 100 segments of epileptic EEG and 100 segments of interictal EEG. A comparison was made between epileptic EEG and interictal EEG in those(More)
Exact localization of the epileptogenic zone (EZ) is the first priority for ensuring epilepsy treatments and reducing side effects. The results of traditional visual methods for localizing the origin of seizures are far from satisfactory in some cases. Signal processing methods could extract substantial information that may complement visual inspection of(More)
A model of coupled neural masses can generate seizure-like events and dynamics similar to those observed during interictal to ictal transitions and thus can be used for theoretical study of the control of epileptic seizures. In an effort to understand the mechanisms underlying epileptic seizures and how to avoid them, we added a control input to this model.(More)
The automated seizure detection in EEG is significant for epilepsy monitoring, diagnosis and rehabilitation. In this study, we evaluated the differences between epileptic EEG and normal EEG by computing some nonlinear features. Correlation Dimension (CD) and Approximate Entropy (ApEn) were calculated for one hundred segments of epileptic EEG and one hundred(More)
Automatic seizure detection plays a significant role in the diagnosis of epilepsy. This paper presents a novel method based on S-transform and singular value decomposition (SVD) for seizure detection. Primarily, S-transform is performed on EEG signals, and the obtained time-frequency matrix is divided into submatrices. Then, the singular values of each(More)
Salinity is a widespread environmental problem limiting productivity and growth of plants. Halophytes which can adapt and resist certain salt stress have various mechanisms to defend the higher salinity and alkalinity, and epigenetic mechanisms especially DNA methylation may play important roles in plant adaptability and plasticity. In this study, we aimed(More)
In this paper, a novel watermarking algorithm for colour image resistant to copy attack is presented. The method proposed is experimented in YUV colour space. The feature describing the original image uniquely is attained from the chroma component of the original colour image. After being scrambled by chaotic sequences, the feature is embedded into the(More)
The neural mass model developed by Lopes da Silva et al. simulates complex dynamics between cortical areas and is able to describe a limit cycle behavior for alpha rhythms in electroencephalography (EEG). In this work, we propose a modified neural mass model that incorporates a time delay. This time-delay model can be used to simulate several different(More)